diff --git a/llama-factory/config/models/Qwen2.5-0.5B-Instruct.yaml b/llama-factory/config/models/Qwen2.5-0.5B-Instruct.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..492d7bbd5e816d44cec0df4a5fcd0d35a765eebb
--- /dev/null
+++ b/llama-factory/config/models/Qwen2.5-0.5B-Instruct.yaml
@@ -0,0 +1,43 @@
+### model
+model_name_or_path: Qwen/Qwen2.5-0.5B-Instruct
+
+### method
+stage: sft
+do_train: true
+finetuning_type: lora
+lora_target: all
+
+### dataset
+dataset: alpaca_mgtv_p2
+template: qwen
+cutoff_len: 8192
+max_samples: 25000
+overwrite_cache: true
+preprocessing_num_workers: 16
+
+### output
+output_dir: saves/Qwen2.5-0.5B-Instruct
+logging_steps: 5
+save_steps: 35
+plot_loss: true
+# overwrite_output_dir: true
+
+### train
+per_device_train_batch_size: 16
+gradient_accumulation_steps: 8
+learning_rate: 1.0e-4
+num_train_epochs: 2.0
+lr_scheduler_type: cosine
+warmup_ratio: 0.1
+bf16: true
+ddp_timeout: 180000000
+
+### eval
+val_size: 0.1
+per_device_eval_batch_size: 1
+eval_strategy: steps
+eval_steps: 35
+
+# report_to: wandb
+report_to: none
+run_name: Qwen2.5-0.5B-Instruct_lora_sft
diff --git a/llama-factory/config/models/Qwen2.5-1.5B-Instruct.yaml b/llama-factory/config/models/Qwen2.5-1.5B-Instruct.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..f4d3fff3174736cd9712575865af44670ba29caa
--- /dev/null
+++ b/llama-factory/config/models/Qwen2.5-1.5B-Instruct.yaml
@@ -0,0 +1,43 @@
+### model
+model_name_or_path: Qwen/Qwen2.5-1.5B-Instruct
+
+### method
+stage: sft
+do_train: true
+finetuning_type: lora
+lora_target: all
+
+### dataset
+dataset: alpaca_mgtv_p2
+template: qwen
+cutoff_len: 8192
+max_samples: 25000
+overwrite_cache: true
+preprocessing_num_workers: 16
+
+### output
+output_dir: saves/Qwen2.5-1.5B-Instruct
+logging_steps: 5
+save_steps: 35
+plot_loss: true
+# overwrite_output_dir: true
+
+### train
+per_device_train_batch_size: 16
+gradient_accumulation_steps: 8
+learning_rate: 1.0e-4
+num_train_epochs: 2.0
+lr_scheduler_type: cosine
+warmup_ratio: 0.1
+bf16: true
+ddp_timeout: 180000000
+
+### eval
+val_size: 0.1
+per_device_eval_batch_size: 1
+eval_strategy: steps
+eval_steps: 35
+
+# report_to: wandb
+report_to: none
+run_name: Qwen2.5-1.5B-Instruct_lora_sft
diff --git a/llama-factory/saves/Qwen2.5-0.5B-Instruct/README.md b/llama-factory/saves/Qwen2.5-0.5B-Instruct/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..37b6ebeb2fc9947dae1afa316369584e1674c3af
--- /dev/null
+++ b/llama-factory/saves/Qwen2.5-0.5B-Instruct/README.md
@@ -0,0 +1,73 @@
+---
+license: other
+library_name: peft
+tags:
+- llama-factory
+- lora
+- generated_from_trainer
+base_model: Qwen/Qwen2.5-0.5B-Instruct
+model-index:
+- name: Qwen2.5-0.5B-Instruct
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# Qwen2.5-0.5B-Instruct
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) on the alpaca_mgtv_p2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2634
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 2.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.4381        | 0.1990 | 35   | 0.3907          |
+| 0.3556        | 0.3980 | 70   | 0.3124          |
+| 0.3228        | 0.5970 | 105  | 0.3359          |
+| 0.3026        | 0.7960 | 140  | 0.2879          |
+| 0.2802        | 0.9950 | 175  | 0.2749          |
+| 0.2645        | 1.1940 | 210  | 0.2682          |
+| 0.3012        | 1.3930 | 245  | 0.2593          |
+| 0.2628        | 1.5920 | 280  | 0.2647          |
+| 0.2493        | 1.7910 | 315  | 0.2653          |
+| 0.2642        | 1.9900 | 350  | 0.2634          |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.43.3
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1
\ No newline at end of file
diff --git a/llama-factory/saves/Qwen2.5-0.5B-Instruct/adapter_config.json b/llama-factory/saves/Qwen2.5-0.5B-Instruct/adapter_config.json
new file mode 100644
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--- /dev/null
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+version https://git-lfs.github.com/spec/v1
+oid sha256:50274fc633d35196b94331c0c7bdb7fd9014c611d430da0631ef5848ba676fb3
+size 727
diff --git a/llama-factory/saves/Qwen2.5-0.5B-Instruct/adapter_model.safetensors b/llama-factory/saves/Qwen2.5-0.5B-Instruct/adapter_model.safetensors
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diff --git a/llama-factory/saves/Qwen2.5-0.5B-Instruct/all_results.json b/llama-factory/saves/Qwen2.5-0.5B-Instruct/all_results.json
new file mode 100644
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--- /dev/null
+++ b/llama-factory/saves/Qwen2.5-0.5B-Instruct/all_results.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7c53b468ad3f40129c611e94b4f9be7284a845ced74b4a6e446e34a856d633d2
+size 367
diff --git a/llama-factory/saves/Qwen2.5-0.5B-Instruct/checkpoint-105/README.md b/llama-factory/saves/Qwen2.5-0.5B-Instruct/checkpoint-105/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..30886db19aae11d43ebfe252b3f3b41e5b22a57b
--- /dev/null
+++ b/llama-factory/saves/Qwen2.5-0.5B-Instruct/checkpoint-105/README.md
@@ -0,0 +1,202 @@
+---
+library_name: peft
+base_model: Qwen/Qwen2.5-0.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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diff --git a/llama-factory/saves/Qwen2.5-0.5B-Instruct/checkpoint-140/README.md b/llama-factory/saves/Qwen2.5-0.5B-Instruct/checkpoint-140/README.md
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-0.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-0.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-0.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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@@ -0,0 +1,202 @@
+---
+library_name: peft
+base_model: Qwen/Qwen2.5-0.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-0.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-0.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-0.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-0.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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@@ -0,0 +1,202 @@
+---
+library_name: peft
+base_model: Qwen/Qwen2.5-0.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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diff --git a/llama-factory/saves/Qwen2.5-1.5B-Instruct/README.md b/llama-factory/saves/Qwen2.5-1.5B-Instruct/README.md
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+---
+license: other
+library_name: peft
+tags:
+- llama-factory
+- lora
+- generated_from_trainer
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+model-index:
+- name: Qwen2.5-1.5B-Instruct
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# Qwen2.5-1.5B-Instruct
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on the alpaca_mgtv_p2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2388
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 2.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.4191        | 0.1990 | 35   | 0.3819          |
+| 0.3251        | 0.3980 | 70   | 0.2896          |
+| 0.3081        | 0.5970 | 105  | 0.2995          |
+| 0.2825        | 0.7960 | 140  | 0.2568          |
+| 0.2693        | 0.9950 | 175  | 0.2491          |
+| 0.2466        | 1.1940 | 210  | 0.2544          |
+| 0.2733        | 1.3930 | 245  | 0.2386          |
+| 0.2396        | 1.5920 | 280  | 0.2390          |
+| 0.2373        | 1.7910 | 315  | 0.2412          |
+| 0.2413        | 1.9900 | 350  | 0.2388          |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.43.3
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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+---
+library_name: peft
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1
\ No newline at end of file
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diff --git a/llama-factory/saves/Qwen2.5-1.5B-Instruct/checkpoint-70/training_args.bin b/llama-factory/saves/Qwen2.5-1.5B-Instruct/checkpoint-70/training_args.bin
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--- /dev/null
+++ b/llama-factory/saves/Qwen2.5-1.5B-Instruct/vocab.json
@@ -0,0 +1,3 @@
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+size 2776833
diff --git a/notebooks/07_Qwen2.5_models.ipynb b/notebooks/07_Qwen2.5_models.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..42630a93416bcba9bbe27212ffd281b8c20610c8
--- /dev/null
+++ b/notebooks/07_Qwen2.5_models.ipynb
@@ -0,0 +1,16726 @@
+{
+    "cells": [
+        {
+            "cell_type": "code",
+            "execution_count": 2,
+            "metadata": {
+                "application/vnd.databricks.v1+cell": {
+                    "cellMetadata": {},
+                    "inputWidgets": {},
+                    "nuid": "0ea8b46b-839b-445b-8043-ccdf4e920ace",
+                    "showTitle": false,
+                    "title": ""
+                },
+                "id": "YLH80COBzi_F"
+            },
+            "outputs": [],
+            "source": [
+                "%load_ext autoreload\n",
+                "%autoreload 2"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 3,
+            "metadata": {
+                "id": "63B5exAuzq4M"
+            },
+            "outputs": [],
+            "source": [
+                "from pathlib import Path\n",
+                "\n",
+                "if \"workding_dir\" not in locals():\n",
+                "    try:\n",
+                "        from google.colab import drive\n",
+                "        drive.mount('/content/drive')\n",
+                "        workding_dir = \"/content/drive/MyDrive/logical-reasoning/\"\n",
+                "    except ModuleNotFoundError:\n",
+                "        workding_dir = str(Path.cwd().parent)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 4,
+            "metadata": {
+                "executionInfo": {
+                    "elapsed": 368,
+                    "status": "ok",
+                    "timestamp": 1719461634865,
+                    "user": {
+                        "displayName": "Donghao Huang",
+                        "userId": "00463591218503521679"
+                    },
+                    "user_tz": -480
+                },
+                "id": "zFulf0bg0H-9",
+                "outputId": "debdd535-c828-40b9-efc0-8a180e5830dd"
+            },
+            "outputs": [
+                {
+                    "name": "stdout",
+                    "output_type": "stream",
+                    "text": [
+                        "workding dir: /home/inflaton/code/logical-reasoning\n"
+                    ]
+                }
+            ],
+            "source": [
+                "import os\n",
+                "import sys\n",
+                "\n",
+                "os.chdir(workding_dir)\n",
+                "sys.path.append(workding_dir)\n",
+                "print(\"workding dir:\", workding_dir)"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 7,
+            "metadata": {
+                "application/vnd.databricks.v1+cell": {
+                    "cellMetadata": {},
+                    "inputWidgets": {},
+                    "nuid": "9f67ec60-2f24-411c-84eb-0dd664b44775",
+                    "showTitle": false,
+                    "title": ""
+                },
+                "colab": {
+                    "base_uri": "https://localhost:8080/"
+                },
+                "executionInfo": {
+                    "elapsed": 589,
+                    "status": "ok",
+                    "timestamp": 1719462011879,
+                    "user": {
+                        "displayName": "Donghao Huang",
+                        "userId": "00463591218503521679"
+                    },
+                    "user_tz": -480
+                },
+                "id": "DIUiweYYzi_I",
+                "outputId": "e16e9247-9077-4b0c-f8ea-17059f05a1c4"
+            },
+            "outputs": [
+                {
+                    "name": "stdout",
+                    "output_type": "stream",
+                    "text": [
+                        "Current Directory:\n",
+                        "/home/inflaton/code/logical-reasoning\n",
+                        "Sat Sep 21 15:45:11 2024       \n",
+                        "+-----------------------------------------------------------------------------------------+\n",
+                        "| NVIDIA-SMI 560.35.02              Driver Version: 560.94         CUDA Version: 12.6     |\n",
+                        "|-----------------------------------------+------------------------+----------------------+\n",
+                        "| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |\n",
+                        "| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |\n",
+                        "|                                         |                        |               MIG M. |\n",
+                        "|=========================================+========================+======================|\n",
+                        "|   0  NVIDIA GeForce RTX 4090        On  |   00000000:01:00.0  On |                  Off |\n",
+                        "| 37%   54C    P8             22W /  450W |     535MiB /  24564MiB |      4%      Default |\n",
+                        "|                                         |                        |                  N/A |\n",
+                        "+-----------------------------------------+------------------------+----------------------+\n",
+                        "                                                                                         \n",
+                        "+-----------------------------------------------------------------------------------------+\n",
+                        "| Processes:                                                                              |\n",
+                        "|  GPU   GI   CI        PID   Type   Process name                              GPU Memory |\n",
+                        "|        ID   ID                                                               Usage      |\n",
+                        "|=========================================================================================|\n",
+                        "|    0   N/A  N/A        25      G   /Xwayland                                   N/A      |\n",
+                        "+-----------------------------------------------------------------------------------------+\n",
+                        "Linux Gen-AI 5.15.133.1-microsoft-standard-WSL2 #1 SMP Thu Oct 5 21:02:42 UTC 2023 x86_64 x86_64 x86_64 GNU/Linux\n",
+                        "PRETTY_NAME=\"Ubuntu 22.04.2 LTS\"\n",
+                        "NAME=\"Ubuntu\"\n",
+                        "VERSION_ID=\"22.04\"\n",
+                        "VERSION=\"22.04.2 LTS (Jammy Jellyfish)\"\n",
+                        "VERSION_CODENAME=jammy\n",
+                        "ID=ubuntu\n",
+                        "ID_LIKE=debian\n",
+                        "HOME_URL=\"https://www.ubuntu.com/\"\n",
+                        "SUPPORT_URL=\"https://help.ubuntu.com/\"\n",
+                        "BUG_REPORT_URL=\"https://bugs.launchpad.net/ubuntu/\"\n",
+                        "PRIVACY_POLICY_URL=\"https://www.ubuntu.com/legal/terms-and-policies/privacy-policy\"\n",
+                        "UBUNTU_CODENAME=jammy\n",
+                        "Architecture:            x86_64\n",
+                        "  CPU op-mode(s):        32-bit, 64-bit\n",
+                        "  Address sizes:         39 bits physical, 48 bits virtual\n",
+                        "  Byte Order:            Little Endian\n",
+                        "CPU(s):                  32\n",
+                        "  On-line CPU(s) list:   0-31\n",
+                        "Vendor ID:               GenuineIntel\n",
+                        "  Model name:            13th Gen Intel(R) Core(TM) i9-13900KF\n",
+                        "    CPU family:          6\n",
+                        "    Model:               183\n",
+                        "    Thread(s) per core:  2\n",
+                        "    Core(s) per socket:  16\n",
+                        "    Socket(s):           1\n",
+                        "    Stepping:            1\n",
+                        "    BogoMIPS:            5990.39\n",
+                        "    Flags:               fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mc\n",
+                        "                         a cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscal\n",
+                        "                         l nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopo\n",
+                        "                         logy tsc_reliable nonstop_tsc cpuid pni pclmulqdq vmx s\n",
+                        "                         sse3 fma cx16 sse4_1 sse4_2 x2apic movbe popcnt tsc_dea\n",
+                        "                         dline_timer aes xsave avx f16c rdrand hypervisor lahf_l\n",
+                        "                         m abm 3dnowprefetch ssbd ibrs ibpb stibp ibrs_enhanced \n",
+                        "                         tpr_shadow vnmi ept vpid ept_ad fsgsbase tsc_adjust bmi\n",
+                        "                         1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushop\n",
+                        "                         t clwb sha_ni xsaveopt xsavec xgetbv1 xsaves avx_vnni u\n",
+                        "                         mip waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64\n",
+                        "                         b fsrm md_clear serialize flush_l1d arch_capabilities\n",
+                        "Virtualization features: \n",
+                        "  Virtualization:        VT-x\n",
+                        "  Hypervisor vendor:     Microsoft\n",
+                        "  Virtualization type:   full\n",
+                        "Caches (sum of all):     \n",
+                        "  L1d:                   768 KiB (16 instances)\n",
+                        "  L1i:                   512 KiB (16 instances)\n",
+                        "  L2:                    32 MiB (16 instances)\n",
+                        "  L3:                    36 MiB (1 instance)\n",
+                        "Vulnerabilities:         \n",
+                        "  Gather data sampling:  Not affected\n",
+                        "  Itlb multihit:         Not affected\n",
+                        "  L1tf:                  Not affected\n",
+                        "  Mds:                   Not affected\n",
+                        "  Meltdown:              Not affected\n",
+                        "  Mmio stale data:       Not affected\n",
+                        "  Retbleed:              Mitigation; Enhanced IBRS\n",
+                        "  Spec rstack overflow:  Not affected\n",
+                        "  Spec store bypass:     Mitigation; Speculative Store Bypass disabled via prctl\n",
+                        "                          and seccomp\n",
+                        "  Spectre v1:            Mitigation; usercopy/swapgs barriers and __user pointer\n",
+                        "                          sanitization\n",
+                        "  Spectre v2:            Mitigation; Enhanced IBRS, IBPB conditional, RSB fillin\n",
+                        "                         g, PBRSB-eIBRS SW sequence\n",
+                        "  Srbds:                 Not affected\n",
+                        "  Tsx async abort:       Not affected\n",
+                        "MemTotal:       49330024 kB\n",
+                        "Current Directory:\n",
+                        "/home/inflaton/code/logical-reasoning/llama-factory\n",
+                        "loading env vars from: /home/inflaton/code/logical-reasoning/.env\n",
+                        "Adding /home/inflaton/code/logical-reasoning to sys.path\n",
+                        "loading /home/inflaton/code/logical-reasoning/llm_toolkit/logical_reasoning_utils.py\n",
+                        "Qwen Qwen2.5-3B-Instruct qwen config/mgtv_template.yaml ../datasets/mgtv\n",
+                        "Writing to config/models/Qwen2.5-3B-Instruct.yaml\n",
+                        "config/models/Qwen2.5-3B-Instruct.yaml:\n",
+                        " {\n",
+                        "  \"model_name_or_path\": \"Qwen/Qwen2.5-3B-Instruct\",\n",
+                        "  \"stage\": \"sft\",\n",
+                        "  \"do_train\": true,\n",
+                        "  \"finetuning_type\": \"lora\",\n",
+                        "  \"lora_target\": \"all\",\n",
+                        "  \"dataset\": \"alpaca_mgtv_p2\",\n",
+                        "  \"template\": \"qwen\",\n",
+                        "  \"cutoff_len\": 8192,\n",
+                        "  \"max_samples\": 25000,\n",
+                        "  \"overwrite_cache\": true,\n",
+                        "  \"preprocessing_num_workers\": 16,\n",
+                        "  \"output_dir\": \"saves/Qwen2.5-3B-Instruct\",\n",
+                        "  \"logging_steps\": 5,\n",
+                        "  \"save_steps\": 35,\n",
+                        "  \"plot_loss\": true,\n",
+                        "  \"per_device_train_batch_size\": 16,\n",
+                        "  \"gradient_accumulation_steps\": 8,\n",
+                        "  \"learning_rate\": 0.0001,\n",
+                        "  \"num_train_epochs\": 2.0,\n",
+                        "  \"lr_scheduler_type\": \"cosine\",\n",
+                        "  \"warmup_ratio\": 0.1,\n",
+                        "  \"bf16\": true,\n",
+                        "  \"ddp_timeout\": 180000000,\n",
+                        "  \"val_size\": 0.1,\n",
+                        "  \"per_device_eval_batch_size\": 1,\n",
+                        "  \"eval_strategy\": \"steps\",\n",
+                        "  \"eval_steps\": 35,\n",
+                        "  \"report_to\": \"none\",\n",
+                        "  \"run_name\": \"Qwen2.5-3B-Instruct_lora_sft\"\n",
+                        "}\n",
+                        "09/21/2024 15:45:22 - INFO - llamafactory.hparams.parser - Process rank: 0, device: cuda:0, n_gpu: 1, distributed training: False, compute dtype: torch.bfloat16\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 15:45:23,254 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-3B-Instruct/snapshots/82f42baa094a9600e39ccd80d34058aeeb3abbc1/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 15:45:23,255 >> Model config Qwen2Config {\n",
+                        "  \"_name_or_path\": \"Qwen/Qwen2.5-3B-Instruct\",\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 2048,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 11008,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 70,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 16,\n",
+                        "  \"num_hidden_layers\": 36,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:45:23,514 >> loading file vocab.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-3B-Instruct/snapshots/82f42baa094a9600e39ccd80d34058aeeb3abbc1/vocab.json\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:45:23,514 >> loading file merges.txt from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-3B-Instruct/snapshots/82f42baa094a9600e39ccd80d34058aeeb3abbc1/merges.txt\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:45:23,514 >> loading file tokenizer.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-3B-Instruct/snapshots/82f42baa094a9600e39ccd80d34058aeeb3abbc1/tokenizer.json\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:45:23,514 >> loading file added_tokens.json from cache at None\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:45:23,514 >> loading file special_tokens_map.json from cache at None\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:45:23,514 >> loading file tokenizer_config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-3B-Instruct/snapshots/82f42baa094a9600e39ccd80d34058aeeb3abbc1/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2533] 2024-09-21 15:45:23,600 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 15:45:24,723 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-3B-Instruct/snapshots/82f42baa094a9600e39ccd80d34058aeeb3abbc1/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 15:45:24,724 >> Model config Qwen2Config {\n",
+                        "  \"_name_or_path\": \"Qwen/Qwen2.5-3B-Instruct\",\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 2048,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 11008,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 70,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 16,\n",
+                        "  \"num_hidden_layers\": 36,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:45:24,997 >> loading file vocab.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-3B-Instruct/snapshots/82f42baa094a9600e39ccd80d34058aeeb3abbc1/vocab.json\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:45:24,997 >> loading file merges.txt from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-3B-Instruct/snapshots/82f42baa094a9600e39ccd80d34058aeeb3abbc1/merges.txt\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:45:24,997 >> loading file tokenizer.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-3B-Instruct/snapshots/82f42baa094a9600e39ccd80d34058aeeb3abbc1/tokenizer.json\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:45:24,997 >> loading file added_tokens.json from cache at None\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:45:24,997 >> loading file special_tokens_map.json from cache at None\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:45:24,997 >> loading file tokenizer_config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-3B-Instruct/snapshots/82f42baa094a9600e39ccd80d34058aeeb3abbc1/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2533] 2024-09-21 15:45:25,089 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n",
+                        "09/21/2024 15:45:25 - INFO - llamafactory.data.template - Replace eos token: <|im_end|>\n",
+                        "09/21/2024 15:45:25 - INFO - llamafactory.data.loader - Loading dataset alpaca_mgtv_p2.json...\n",
+                        "Converting format of dataset (num_proc=16): 100%|█| 25000/25000 [00:00<00:00, 11\n",
+                        "Running tokenizer on dataset (num_proc=16): 100%|█| 25000/25000 [00:01<00:00, 16\n",
+                        "training example:\n",
+                        "input_ids:\n",
+                        "[151644, 8948, 198, 2610, 525, 264, 10950, 17847, 13, 151645, 198, 151644, 872, 198, 56568, 101909, 108024, 101497, 107969, 99329, 9370, 106040, 1773, 99329, 104190, 104506, 48443, 16, 13, 26853, 224, 57218, 28946, 36993, 101051, 46944, 107969, 27091, 3837, 107969, 27091, 36993, 53481, 46944, 100405, 99518, 104151, 101128, 9370, 57621, 8997, 17, 13, 89982, 68878, 17340, 99392, 107969, 99413, 3837, 107969, 99413, 20412, 107969, 27091, 111230, 8997, 18, 13, 26853, 224, 57218, 28946, 73670, 105396, 99885, 106386, 28330, 86119, 112469, 100246, 57621, 9370, 106538, 8997, 19, 13, 69162, 34204, 103991, 86119, 3837, 106040, 44063, 100345, 107591, 102104, 87752, 105220, 109487, 100653, 5122, 20412, 5373, 99520, 5373, 16530, 99335, 5373, 102104, 88991, 5373, 56007, 24339, 32100, 1773, 99200, 102104, 9370, 104317, 100142, 104506, 28311, 256, 481, 92498, 107969, 27091, 33108, 107969, 99413, 114562, 86119, 111230, 3837, 102104, 5122, 20412, 100631, 99520, 198, 256, 481, 92498, 107969, 27091, 33108, 107969, 99413, 53153, 101041, 100631, 108349, 83751, 63789, 20221, 86119, 111230, 3837, 102104, 5122, 16530, 99335, 198, 256, 481, 92498, 111842, 107666, 113479, 106386, 28330, 86119, 100631, 86119, 104151, 101128, 3837, 102104, 5122, 56007, 24339, 32100, 198, 256, 481, 92498, 111842, 107666, 99797, 108670, 34187, 107969, 99413, 106538, 3837, 102104, 5122, 102104, 88991, 198, 20, 13, 49602, 252, 99590, 15946, 53153, 42855, 99885, 102158, 27369, 3837, 105827, 65770, 99475, 109487, 101047, 110281, 18600, 1773, 77557, 3837, 108620, 99360, 2073, 99520, 854, 65770, 99475, 12857, 2073, 16530, 96332, 14880, 110439, 100001, 104190, 102104, 111842, 101080, 103936, 3407, 334, 107969, 27091, 66963, 73562, 109628, 45629, 105489, 3837, 104133, 111718, 106023, 5122, 101988, 115865, 110731, 9370, 105419, 3837, 115865, 99810, 69249, 59743, 104133, 104003, 115865, 36993, 16530, 101401, 68536, 99723, 3837, 115967, 104270, 102060, 110666, 112031, 1773, 14880, 109363, 115865, 110786, 101423, 104249, 3407, 334, 107969, 99413, 66963, 10236, 250, 253, 48921, 101221, 57218, 101961, 7948, 100894, 9370, 99288, 99818, 101063, 1773, 104269, 99288, 99818, 100774, 13343, 3837, 99798, 57218, 101961, 105664, 102373, 48921, 100271, 1773, 99650, 105616, 18493, 115865, 110731, 9370, 105419, 104388, 1773, 103968, 3837, 102606, 102115, 17340, 3837, 102373, 18493, 106340, 24562, 99774, 82224, 104424, 15946, 99372, 99244, 1773, 110597, 9370, 99288, 99818, 100012, 101416, 63109, 99242, 9370, 102373, 3837, 101988, 101938, 44063, 104003, 115865, 101329, 99314, 3837, 107974, 102373, 9370, 104575, 24562, 3837, 105699, 116418, 100005, 103000, 90663, 1773, 100147, 101070, 105443, 34187, 100097, 3837, 104989, 100833, 69249, 46944, 105190, 9370, 106023, 3407, 334, 111842, 101080, 103936, 66963, 4891, 223, 115, 100623, 21317, 99315, 101037, 198, 151645, 198, 151644, 77091, 198, 99520, 151645]\n",
+                        "inputs:\n",
+                        "<|im_start|>system\n",
+                        "You are a helpful assistant.<|im_end|>\n",
+                        "<|im_start|>user\n",
+                        "你是一个情景猜谜游戏的主持人。游戏规则如下：\n",
+                        "\n",
+                        "1. 参与者会得到一个谜面，谜面会描述一个简单又难以理解的事件。\n",
+                        "2. 主持人知道谜底，谜底是谜面的答案。\n",
+                        "3. 参与者可以询问任何封闭式问题来找寻事件的真相。\n",
+                        "4. 对于每个问题，主持人将根据实际情况回答以下五个选项之一：是、不是、不重要、回答正确、问法错误。各回答的判断标准如下：\n",
+                        "   - 若谜面和谜底能找到问题的答案，回答：是或者不是\n",
+                        "   - 若谜面和谜底不能直接或者间接推断出问题的答案，回答：不重要\n",
+                        "   - 若参与者提问不是一个封闭式问题或者问题难以理解，回答：问法错误\n",
+                        "   - 若参与者提问基本还原了谜底真相，回答：回答正确\n",
+                        "5. 回答中不能添加任何其它信息，也不能省略选项中的任何一个字。例如，不可以把“不是”省略成“不”。\n",
+                        "\n",
+                        "请严格按照这些规则回答参与者提出的问题。\n",
+                        "\n",
+                        "**谜面:** 在甄家村里，有一个古老的传说：每年南瓜丰收的季节，南瓜田里总有一个最大的南瓜会不翼而飞，村民们对此现象困惑不解。请找出南瓜失踪背后的原因。\n",
+                        "\n",
+                        "**谜底:** 真相原来与一位年迈的农夫有关。这位农夫年轻时，曾与一位美丽的姑娘相恋。他们约定在南瓜丰收的季节结婚。然而，命运弄人，姑娘在婚礼前的一场意外中离世。悲伤的农夫为了纪念心爱的姑娘，每年都会将最大的南瓜偷走，放到姑娘的墓前，以此寄托自己的哀思。这一行为延续了多年，成为了乡村里一个神秘的传说。\n",
+                        "\n",
+                        "**参与者提出的问题:** 偷的人信神吗\n",
+                        "<|im_end|>\n",
+                        "<|im_start|>assistant\n",
+                        "不是<|im_end|>\n",
+                        "label_ids:\n",
+                        "[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 99520, 151645]\n",
+                        "labels:\n",
+                        "不是<|im_end|>\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 15:45:28,548 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-3B-Instruct/snapshots/82f42baa094a9600e39ccd80d34058aeeb3abbc1/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 15:45:28,548 >> Model config Qwen2Config {\n",
+                        "  \"_name_or_path\": \"Qwen/Qwen2.5-3B-Instruct\",\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 2048,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 11008,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 70,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 16,\n",
+                        "  \"num_hidden_layers\": 36,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|modeling_utils.py:3634] 2024-09-21 15:45:28,559 >> loading weights file model.safetensors from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-3B-Instruct/snapshots/82f42baa094a9600e39ccd80d34058aeeb3abbc1/model.safetensors.index.json\n",
+                        "[INFO|modeling_utils.py:1572] 2024-09-21 15:45:28,560 >> Instantiating Qwen2ForCausalLM model under default dtype torch.bfloat16.\n",
+                        "[INFO|configuration_utils.py:1038] 2024-09-21 15:45:28,560 >> Generate config GenerationConfig {\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645\n",
+                        "}\n",
+                        "\n",
+                        "Loading checkpoint shards: 100%|██████████████████| 2/2 [00:39<00:00, 19.96s/it]\n",
+                        "[INFO|modeling_utils.py:4463] 2024-09-21 15:46:08,667 >> All model checkpoint weights were used when initializing Qwen2ForCausalLM.\n",
+                        "\n",
+                        "[INFO|modeling_utils.py:4471] 2024-09-21 15:46:08,667 >> All the weights of Qwen2ForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-3B-Instruct.\n",
+                        "If your task is similar to the task the model of the checkpoint was trained on, you can already use Qwen2ForCausalLM for predictions without further training.\n",
+                        "[INFO|configuration_utils.py:993] 2024-09-21 15:46:08,922 >> loading configuration file generation_config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-3B-Instruct/snapshots/82f42baa094a9600e39ccd80d34058aeeb3abbc1/generation_config.json\n",
+                        "[INFO|configuration_utils.py:1038] 2024-09-21 15:46:08,922 >> Generate config GenerationConfig {\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"do_sample\": true,\n",
+                        "  \"eos_token_id\": [\n",
+                        "    151645,\n",
+                        "    151643\n",
+                        "  ],\n",
+                        "  \"pad_token_id\": 151643,\n",
+                        "  \"repetition_penalty\": 1.05,\n",
+                        "  \"temperature\": 0.7,\n",
+                        "  \"top_k\": 20,\n",
+                        "  \"top_p\": 0.8\n",
+                        "}\n",
+                        "\n",
+                        "09/21/2024 15:46:09 - INFO - llamafactory.model.model_utils.checkpointing - Gradient checkpointing enabled.\n",
+                        "09/21/2024 15:46:09 - INFO - llamafactory.model.model_utils.attention - Using torch SDPA for faster training and inference.\n",
+                        "09/21/2024 15:46:09 - INFO - llamafactory.model.adapter - Upcasting trainable params to float32.\n",
+                        "09/21/2024 15:46:09 - INFO - llamafactory.model.adapter - Fine-tuning method: LoRA\n",
+                        "09/21/2024 15:46:09 - INFO - llamafactory.model.model_utils.misc - Found linear modules: v_proj,q_proj,k_proj,up_proj,gate_proj,down_proj,o_proj\n",
+                        "09/21/2024 15:46:09 - INFO - llamafactory.model.loader - trainable params: 14,966,784 || all params: 3,100,905,472 || trainable%: 0.4827\n",
+                        "[INFO|trainer.py:648] 2024-09-21 15:46:09,435 >> Using auto half precision backend\n",
+                        "[INFO|trainer.py:2134] 2024-09-21 15:46:09,741 >> ***** Running training *****\n",
+                        "[INFO|trainer.py:2135] 2024-09-21 15:46:09,741 >>   Num examples = 22,500\n",
+                        "[INFO|trainer.py:2136] 2024-09-21 15:46:09,741 >>   Num Epochs = 2\n",
+                        "[INFO|trainer.py:2137] 2024-09-21 15:46:09,741 >>   Instantaneous batch size per device = 16\n",
+                        "[INFO|trainer.py:2140] 2024-09-21 15:46:09,741 >>   Total train batch size (w. parallel, distributed & accumulation) = 128\n",
+                        "[INFO|trainer.py:2141] 2024-09-21 15:46:09,741 >>   Gradient Accumulation steps = 8\n",
+                        "[INFO|trainer.py:2142] 2024-09-21 15:46:09,741 >>   Total optimization steps = 350\n",
+                        "[INFO|trainer.py:2143] 2024-09-21 15:46:09,743 >>   Number of trainable parameters = 14,966,784\n",
+                        "  0%|                                                   | 0/350 [00:00<?, ?it/s]Traceback (most recent call last):\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/bin/llamafactory-cli\", line 8, in <module>\n",
+                        "    sys.exit(main())\n",
+                        "             ^^^^^^\n",
+                        "  File \"/home/inflaton/code/LLaMA-Factory/src/llamafactory/cli.py\", line 111, in main\n",
+                        "    run_exp()\n",
+                        "  File \"/home/inflaton/code/LLaMA-Factory/src/llamafactory/train/tuner.py\", line 50, in run_exp\n",
+                        "    run_sft(model_args, data_args, training_args, finetuning_args, generating_args, callbacks)\n",
+                        "  File \"/home/inflaton/code/LLaMA-Factory/src/llamafactory/train/sft/workflow.py\", line 96, in run_sft\n",
+                        "    train_result = trainer.train(resume_from_checkpoint=training_args.resume_from_checkpoint)\n",
+                        "                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/transformers/trainer.py\", line 1938, in train\n",
+                        "    return inner_training_loop(\n",
+                        "           ^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/transformers/trainer.py\", line 2279, in _inner_training_loop\n",
+                        "    tr_loss_step = self.training_step(model, inputs)\n",
+                        "                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/transformers/trainer.py\", line 3318, in training_step\n",
+                        "    loss = self.compute_loss(model, inputs)\n",
+                        "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/transformers/trainer.py\", line 3363, in compute_loss\n",
+                        "    outputs = model(**inputs)\n",
+                        "              ^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1532, in _wrapped_call_impl\n",
+                        "    return self._call_impl(*args, **kwargs)\n",
+                        "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1541, in _call_impl\n",
+                        "    return forward_call(*args, **kwargs)\n",
+                        "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/accelerate/utils/operations.py\", line 819, in forward\n",
+                        "    return model_forward(*args, **kwargs)\n",
+                        "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/accelerate/utils/operations.py\", line 807, in __call__\n",
+                        "    return convert_to_fp32(self.model_forward(*args, **kwargs))\n",
+                        "                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/torch/amp/autocast_mode.py\", line 16, in decorate_autocast\n",
+                        "    return func(*args, **kwargs)\n",
+                        "           ^^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/peft/peft_model.py\", line 1430, in forward\n",
+                        "    return self.base_model(\n",
+                        "           ^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1532, in _wrapped_call_impl\n",
+                        "    return self._call_impl(*args, **kwargs)\n",
+                        "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1541, in _call_impl\n",
+                        "    return forward_call(*args, **kwargs)\n",
+                        "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/peft/tuners/tuners_utils.py\", line 179, in forward\n",
+                        "    return self.model.forward(*args, **kwargs)\n",
+                        "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/transformers/models/qwen2/modeling_qwen2.py\", line 1082, in forward\n",
+                        "    loss = loss_fct(shift_logits, shift_labels)\n",
+                        "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1532, in _wrapped_call_impl\n",
+                        "    return self._call_impl(*args, **kwargs)\n",
+                        "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/torch/nn/modules/module.py\", line 1541, in _call_impl\n",
+                        "    return forward_call(*args, **kwargs)\n",
+                        "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/torch/nn/modules/loss.py\", line 1185, in forward\n",
+                        "    return F.cross_entropy(input, target, weight=self.weight,\n",
+                        "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+                        "  File \"/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/torch/nn/functional.py\", line 3086, in cross_entropy\n",
+                        "    return torch._C._nn.cross_entropy_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index, label_smoothing)\n",
+                        "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+                        "RuntimeError: CUDA driver error: out of memory\n",
+                        "  0%|                                                   | 0/350 [00:05<?, ?it/s]\n",
+                        "Current Directory:\n",
+                        "/home/inflaton/code/logical-reasoning/llama-factory\n",
+                        "loading env vars from: /home/inflaton/code/logical-reasoning/.env\n",
+                        "Adding /home/inflaton/code/logical-reasoning to sys.path\n",
+                        "loading /home/inflaton/code/logical-reasoning/llm_toolkit/logical_reasoning_utils.py\n",
+                        "Qwen Qwen2.5-1.5B-Instruct qwen config/mgtv_template.yaml ../datasets/mgtv\n",
+                        "Writing to config/models/Qwen2.5-1.5B-Instruct.yaml\n",
+                        "config/models/Qwen2.5-1.5B-Instruct.yaml:\n",
+                        " {\n",
+                        "  \"model_name_or_path\": \"Qwen/Qwen2.5-1.5B-Instruct\",\n",
+                        "  \"stage\": \"sft\",\n",
+                        "  \"do_train\": true,\n",
+                        "  \"finetuning_type\": \"lora\",\n",
+                        "  \"lora_target\": \"all\",\n",
+                        "  \"dataset\": \"alpaca_mgtv_p2\",\n",
+                        "  \"template\": \"qwen\",\n",
+                        "  \"cutoff_len\": 8192,\n",
+                        "  \"max_samples\": 25000,\n",
+                        "  \"overwrite_cache\": true,\n",
+                        "  \"preprocessing_num_workers\": 16,\n",
+                        "  \"output_dir\": \"saves/Qwen2.5-1.5B-Instruct\",\n",
+                        "  \"logging_steps\": 5,\n",
+                        "  \"save_steps\": 35,\n",
+                        "  \"plot_loss\": true,\n",
+                        "  \"per_device_train_batch_size\": 16,\n",
+                        "  \"gradient_accumulation_steps\": 8,\n",
+                        "  \"learning_rate\": 0.0001,\n",
+                        "  \"num_train_epochs\": 2.0,\n",
+                        "  \"lr_scheduler_type\": \"cosine\",\n",
+                        "  \"warmup_ratio\": 0.1,\n",
+                        "  \"bf16\": true,\n",
+                        "  \"ddp_timeout\": 180000000,\n",
+                        "  \"val_size\": 0.1,\n",
+                        "  \"per_device_eval_batch_size\": 1,\n",
+                        "  \"eval_strategy\": \"steps\",\n",
+                        "  \"eval_steps\": 35,\n",
+                        "  \"report_to\": \"none\",\n",
+                        "  \"run_name\": \"Qwen2.5-1.5B-Instruct_lora_sft\"\n",
+                        "}\n",
+                        "09/21/2024 15:46:21 - INFO - llamafactory.hparams.parser - Process rank: 0, device: cuda:0, n_gpu: 1, distributed training: False, compute dtype: torch.bfloat16\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 15:46:21,867 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 15:46:21,868 >> Model config Qwen2Config {\n",
+                        "  \"_name_or_path\": \"Qwen/Qwen2.5-1.5B-Instruct\",\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 1536,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 8960,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 12,\n",
+                        "  \"num_hidden_layers\": 28,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:46:22,126 >> loading file vocab.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/vocab.json\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:46:22,127 >> loading file merges.txt from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/merges.txt\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:46:22,127 >> loading file tokenizer.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/tokenizer.json\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:46:22,127 >> loading file added_tokens.json from cache at None\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:46:22,127 >> loading file special_tokens_map.json from cache at None\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:46:22,127 >> loading file tokenizer_config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2533] 2024-09-21 15:46:22,222 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 15:46:23,467 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 15:46:23,468 >> Model config Qwen2Config {\n",
+                        "  \"_name_or_path\": \"Qwen/Qwen2.5-1.5B-Instruct\",\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 1536,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 8960,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 12,\n",
+                        "  \"num_hidden_layers\": 28,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:46:23,726 >> loading file vocab.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/vocab.json\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:46:23,726 >> loading file merges.txt from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/merges.txt\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:46:23,726 >> loading file tokenizer.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/tokenizer.json\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:46:23,726 >> loading file added_tokens.json from cache at None\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:46:23,726 >> loading file special_tokens_map.json from cache at None\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 15:46:23,726 >> loading file tokenizer_config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2533] 2024-09-21 15:46:23,811 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n",
+                        "09/21/2024 15:46:23 - INFO - llamafactory.data.template - Replace eos token: <|im_end|>\n",
+                        "09/21/2024 15:46:23 - INFO - llamafactory.data.loader - Loading dataset alpaca_mgtv_p2.json...\n",
+                        "Converting format of dataset (num_proc=16): 100%|█| 25000/25000 [00:00<00:00, 11\n",
+                        "Running tokenizer on dataset (num_proc=16): 100%|█| 25000/25000 [00:01<00:00, 16\n",
+                        "training example:\n",
+                        "input_ids:\n",
+                        "[151644, 8948, 198, 2610, 525, 264, 10950, 17847, 13, 151645, 198, 151644, 872, 198, 56568, 101909, 108024, 101497, 107969, 99329, 9370, 106040, 1773, 99329, 104190, 104506, 48443, 16, 13, 26853, 224, 57218, 28946, 36993, 101051, 46944, 107969, 27091, 3837, 107969, 27091, 36993, 53481, 46944, 100405, 99518, 104151, 101128, 9370, 57621, 8997, 17, 13, 89982, 68878, 17340, 99392, 107969, 99413, 3837, 107969, 99413, 20412, 107969, 27091, 111230, 8997, 18, 13, 26853, 224, 57218, 28946, 73670, 105396, 99885, 106386, 28330, 86119, 112469, 100246, 57621, 9370, 106538, 8997, 19, 13, 69162, 34204, 103991, 86119, 3837, 106040, 44063, 100345, 107591, 102104, 87752, 105220, 109487, 100653, 5122, 20412, 5373, 99520, 5373, 16530, 99335, 5373, 102104, 88991, 5373, 56007, 24339, 32100, 1773, 99200, 102104, 9370, 104317, 100142, 104506, 28311, 256, 481, 92498, 107969, 27091, 33108, 107969, 99413, 114562, 86119, 111230, 3837, 102104, 5122, 20412, 100631, 99520, 198, 256, 481, 92498, 107969, 27091, 33108, 107969, 99413, 53153, 101041, 100631, 108349, 83751, 63789, 20221, 86119, 111230, 3837, 102104, 5122, 16530, 99335, 198, 256, 481, 92498, 111842, 107666, 113479, 106386, 28330, 86119, 100631, 86119, 104151, 101128, 3837, 102104, 5122, 56007, 24339, 32100, 198, 256, 481, 92498, 111842, 107666, 99797, 108670, 34187, 107969, 99413, 106538, 3837, 102104, 5122, 102104, 88991, 198, 20, 13, 49602, 252, 99590, 15946, 53153, 42855, 99885, 102158, 27369, 3837, 105827, 65770, 99475, 109487, 101047, 110281, 18600, 1773, 77557, 3837, 108620, 99360, 2073, 99520, 854, 65770, 99475, 12857, 2073, 16530, 96332, 14880, 110439, 100001, 104190, 102104, 111842, 101080, 103936, 3407, 334, 107969, 27091, 66963, 73562, 109628, 45629, 105489, 3837, 104133, 111718, 106023, 5122, 101988, 115865, 110731, 9370, 105419, 3837, 115865, 99810, 69249, 59743, 104133, 104003, 115865, 36993, 16530, 101401, 68536, 99723, 3837, 115967, 104270, 102060, 110666, 112031, 1773, 14880, 109363, 115865, 110786, 101423, 104249, 3407, 334, 107969, 99413, 66963, 10236, 250, 253, 48921, 101221, 57218, 101961, 7948, 100894, 9370, 99288, 99818, 101063, 1773, 104269, 99288, 99818, 100774, 13343, 3837, 99798, 57218, 101961, 105664, 102373, 48921, 100271, 1773, 99650, 105616, 18493, 115865, 110731, 9370, 105419, 104388, 1773, 103968, 3837, 102606, 102115, 17340, 3837, 102373, 18493, 106340, 24562, 99774, 82224, 104424, 15946, 99372, 99244, 1773, 110597, 9370, 99288, 99818, 100012, 101416, 63109, 99242, 9370, 102373, 3837, 101988, 101938, 44063, 104003, 115865, 101329, 99314, 3837, 107974, 102373, 9370, 104575, 24562, 3837, 105699, 116418, 100005, 103000, 90663, 1773, 100147, 101070, 105443, 34187, 100097, 3837, 104989, 100833, 69249, 46944, 105190, 9370, 106023, 3407, 334, 111842, 101080, 103936, 66963, 4891, 223, 115, 100623, 21317, 99315, 101037, 198, 151645, 198, 151644, 77091, 198, 99520, 151645]\n",
+                        "inputs:\n",
+                        "<|im_start|>system\n",
+                        "You are a helpful assistant.<|im_end|>\n",
+                        "<|im_start|>user\n",
+                        "你是一个情景猜谜游戏的主持人。游戏规则如下：\n",
+                        "\n",
+                        "1. 参与者会得到一个谜面，谜面会描述一个简单又难以理解的事件。\n",
+                        "2. 主持人知道谜底，谜底是谜面的答案。\n",
+                        "3. 参与者可以询问任何封闭式问题来找寻事件的真相。\n",
+                        "4. 对于每个问题，主持人将根据实际情况回答以下五个选项之一：是、不是、不重要、回答正确、问法错误。各回答的判断标准如下：\n",
+                        "   - 若谜面和谜底能找到问题的答案，回答：是或者不是\n",
+                        "   - 若谜面和谜底不能直接或者间接推断出问题的答案，回答：不重要\n",
+                        "   - 若参与者提问不是一个封闭式问题或者问题难以理解，回答：问法错误\n",
+                        "   - 若参与者提问基本还原了谜底真相，回答：回答正确\n",
+                        "5. 回答中不能添加任何其它信息，也不能省略选项中的任何一个字。例如，不可以把“不是”省略成“不”。\n",
+                        "\n",
+                        "请严格按照这些规则回答参与者提出的问题。\n",
+                        "\n",
+                        "**谜面:** 在甄家村里，有一个古老的传说：每年南瓜丰收的季节，南瓜田里总有一个最大的南瓜会不翼而飞，村民们对此现象困惑不解。请找出南瓜失踪背后的原因。\n",
+                        "\n",
+                        "**谜底:** 真相原来与一位年迈的农夫有关。这位农夫年轻时，曾与一位美丽的姑娘相恋。他们约定在南瓜丰收的季节结婚。然而，命运弄人，姑娘在婚礼前的一场意外中离世。悲伤的农夫为了纪念心爱的姑娘，每年都会将最大的南瓜偷走，放到姑娘的墓前，以此寄托自己的哀思。这一行为延续了多年，成为了乡村里一个神秘的传说。\n",
+                        "\n",
+                        "**参与者提出的问题:** 偷的人信神吗\n",
+                        "<|im_end|>\n",
+                        "<|im_start|>assistant\n",
+                        "不是<|im_end|>\n",
+                        "label_ids:\n",
+                        "[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 99520, 151645]\n",
+                        "labels:\n",
+                        "不是<|im_end|>\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 15:46:27,182 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 15:46:27,182 >> Model config Qwen2Config {\n",
+                        "  \"_name_or_path\": \"Qwen/Qwen2.5-1.5B-Instruct\",\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 1536,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 8960,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 12,\n",
+                        "  \"num_hidden_layers\": 28,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|modeling_utils.py:3634] 2024-09-21 15:46:27,194 >> loading weights file model.safetensors from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/model.safetensors\n",
+                        "[INFO|modeling_utils.py:1572] 2024-09-21 15:46:27,198 >> Instantiating Qwen2ForCausalLM model under default dtype torch.bfloat16.\n",
+                        "[INFO|configuration_utils.py:1038] 2024-09-21 15:46:27,199 >> Generate config GenerationConfig {\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|modeling_utils.py:4463] 2024-09-21 15:46:57,790 >> All model checkpoint weights were used when initializing Qwen2ForCausalLM.\n",
+                        "\n",
+                        "[INFO|modeling_utils.py:4471] 2024-09-21 15:46:57,790 >> All the weights of Qwen2ForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-1.5B-Instruct.\n",
+                        "If your task is similar to the task the model of the checkpoint was trained on, you can already use Qwen2ForCausalLM for predictions without further training.\n",
+                        "[INFO|configuration_utils.py:993] 2024-09-21 15:46:58,065 >> loading configuration file generation_config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/generation_config.json\n",
+                        "[INFO|configuration_utils.py:1038] 2024-09-21 15:46:58,066 >> Generate config GenerationConfig {\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"do_sample\": true,\n",
+                        "  \"eos_token_id\": [\n",
+                        "    151645,\n",
+                        "    151643\n",
+                        "  ],\n",
+                        "  \"pad_token_id\": 151643,\n",
+                        "  \"repetition_penalty\": 1.1,\n",
+                        "  \"temperature\": 0.7,\n",
+                        "  \"top_k\": 20,\n",
+                        "  \"top_p\": 0.8\n",
+                        "}\n",
+                        "\n",
+                        "09/21/2024 15:46:58 - INFO - llamafactory.model.model_utils.checkpointing - Gradient checkpointing enabled.\n",
+                        "09/21/2024 15:46:58 - INFO - llamafactory.model.model_utils.attention - Using torch SDPA for faster training and inference.\n",
+                        "09/21/2024 15:46:58 - INFO - llamafactory.model.adapter - Upcasting trainable params to float32.\n",
+                        "09/21/2024 15:46:58 - INFO - llamafactory.model.adapter - Fine-tuning method: LoRA\n",
+                        "09/21/2024 15:46:58 - INFO - llamafactory.model.model_utils.misc - Found linear modules: up_proj,k_proj,o_proj,down_proj,gate_proj,v_proj,q_proj\n",
+                        "09/21/2024 15:46:58 - INFO - llamafactory.model.loader - trainable params: 9,232,384 || all params: 1,552,946,688 || trainable%: 0.5945\n",
+                        "[INFO|trainer.py:648] 2024-09-21 15:46:58,533 >> Using auto half precision backend\n",
+                        "[INFO|trainer.py:2134] 2024-09-21 15:46:58,837 >> ***** Running training *****\n",
+                        "[INFO|trainer.py:2135] 2024-09-21 15:46:58,837 >>   Num examples = 22,500\n",
+                        "[INFO|trainer.py:2136] 2024-09-21 15:46:58,837 >>   Num Epochs = 2\n",
+                        "[INFO|trainer.py:2137] 2024-09-21 15:46:58,837 >>   Instantaneous batch size per device = 16\n",
+                        "[INFO|trainer.py:2140] 2024-09-21 15:46:58,837 >>   Total train batch size (w. parallel, distributed & accumulation) = 128\n",
+                        "[INFO|trainer.py:2141] 2024-09-21 15:46:58,837 >>   Gradient Accumulation steps = 8\n",
+                        "[INFO|trainer.py:2142] 2024-09-21 15:46:58,837 >>   Total optimization steps = 350\n",
+                        "[INFO|trainer.py:2143] 2024-09-21 15:46:58,839 >>   Number of trainable parameters = 9,232,384\n",
+                        "{'loss': 0.8917, 'grad_norm': 6.9668869972229, 'learning_rate': 1.4285714285714285e-05, 'epoch': 0.03}\n",
+                        "{'loss': 0.7893, 'grad_norm': 4.941070079803467, 'learning_rate': 2.857142857142857e-05, 'epoch': 0.06}\n",
+                        "{'loss': 0.5842, 'grad_norm': 2.900670051574707, 'learning_rate': 4.2857142857142856e-05, 'epoch': 0.09}\n",
+                        "{'loss': 0.5452, 'grad_norm': 1.3792134523391724, 'learning_rate': 5.714285714285714e-05, 'epoch': 0.11}\n",
+                        "{'loss': 0.5008, 'grad_norm': 2.0141210556030273, 'learning_rate': 7.142857142857143e-05, 'epoch': 0.14}\n",
+                        "{'loss': 0.4601, 'grad_norm': 1.0095895528793335, 'learning_rate': 8.571428571428571e-05, 'epoch': 0.17}\n",
+                        "{'loss': 0.4191, 'grad_norm': 1.0098716020584106, 'learning_rate': 0.0001, 'epoch': 0.2}\n",
+                        " 10%|████▏                                     | 35/350 [05:32<49:55,  9.51s/it][INFO|trainer.py:3819] 2024-09-21 15:52:31,446 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 15:52:31,446 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 15:52:31,446 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.3818928301334381, 'eval_runtime': 89.9679, 'eval_samples_per_second': 27.788, 'eval_steps_per_second': 27.788, 'epoch': 0.2}\n",
+                        " 10%|████▏                                     | 35/350 [07:02<49:55,  9.51s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 15:54:01,414 >> Saving model checkpoint to saves/Qwen2.5-1.5B-Instruct/checkpoint-35\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 15:54:02,730 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 15:54:02,731 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 1536,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 8960,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 12,\n",
+                        "  \"num_hidden_layers\": 28,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 15:54:02,777 >> tokenizer config file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-35/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 15:54:02,777 >> Special tokens file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-35/special_tokens_map.json\n",
+                        "{'loss': 0.3736, 'grad_norm': 0.5351007580757141, 'learning_rate': 9.993784606094612e-05, 'epoch': 0.23}\n",
+                        "{'loss': 0.3715, 'grad_norm': 0.634586751461029, 'learning_rate': 9.975153876827008e-05, 'epoch': 0.26}\n",
+                        "{'loss': 0.372, 'grad_norm': 0.5977622270584106, 'learning_rate': 9.944154131125642e-05, 'epoch': 0.28}\n",
+                        "{'loss': 0.3397, 'grad_norm': 0.709690272808075, 'learning_rate': 9.900862439242719e-05, 'epoch': 0.31}\n",
+                        "{'loss': 0.3459, 'grad_norm': 0.4649967849254608, 'learning_rate': 9.84538643114539e-05, 'epoch': 0.34}\n",
+                        "{'loss': 0.3089, 'grad_norm': 0.6929703950881958, 'learning_rate': 9.777864028930705e-05, 'epoch': 0.37}\n",
+                        "{'loss': 0.3251, 'grad_norm': 0.762086033821106, 'learning_rate': 9.698463103929542e-05, 'epoch': 0.4}\n",
+                        " 20%|████████▍                                 | 70/350 [12:40<44:20,  9.50s/it][INFO|trainer.py:3819] 2024-09-21 15:59:39,607 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 15:59:39,608 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 15:59:39,608 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.28960347175598145, 'eval_runtime': 90.1511, 'eval_samples_per_second': 27.731, 'eval_steps_per_second': 27.731, 'epoch': 0.4}\n",
+                        " 20%|████████▍                                 | 70/350 [14:10<44:20,  9.50s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 16:01:09,759 >> Saving model checkpoint to saves/Qwen2.5-1.5B-Instruct/checkpoint-70\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 16:01:11,066 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 16:01:11,067 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 1536,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 8960,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 12,\n",
+                        "  \"num_hidden_layers\": 28,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 16:01:11,111 >> tokenizer config file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-70/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 16:01:11,111 >> Special tokens file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-70/special_tokens_map.json\n",
+                        "{'loss': 0.3082, 'grad_norm': 0.8383176922798157, 'learning_rate': 9.607381059352038e-05, 'epoch': 0.43}\n",
+                        "{'loss': 0.2929, 'grad_norm': 0.8879653215408325, 'learning_rate': 9.504844339512095e-05, 'epoch': 0.45}\n",
+                        "{'loss': 0.3087, 'grad_norm': 1.3542834520339966, 'learning_rate': 9.391107866851143e-05, 'epoch': 0.48}\n",
+                        "{'loss': 0.2889, 'grad_norm': 0.4832295775413513, 'learning_rate': 9.266454408160779e-05, 'epoch': 0.51}\n",
+                        "{'loss': 0.2977, 'grad_norm': 0.7334930896759033, 'learning_rate': 9.131193871579975e-05, 'epoch': 0.54}\n",
+                        "{'loss': 0.284, 'grad_norm': 0.9593209624290466, 'learning_rate': 8.985662536114613e-05, 'epoch': 0.57}\n",
+                        "{'loss': 0.3081, 'grad_norm': 0.6446382403373718, 'learning_rate': 8.83022221559489e-05, 'epoch': 0.6}\n",
+                        " 30%|████████████▎                            | 105/350 [19:45<38:35,  9.45s/it][INFO|trainer.py:3819] 2024-09-21 16:06:43,938 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 16:06:43,938 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 16:06:43,938 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.29949715733528137, 'eval_runtime': 90.8184, 'eval_samples_per_second': 27.527, 'eval_steps_per_second': 27.527, 'epoch': 0.6}\n",
+                        " 30%|████████████▎                            | 105/350 [21:15<38:35,  9.45s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 16:08:14,757 >> Saving model checkpoint to saves/Qwen2.5-1.5B-Instruct/checkpoint-105\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 16:08:46,048 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 16:08:46,049 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 1536,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 8960,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 12,\n",
+                        "  \"num_hidden_layers\": 28,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 16:08:46,094 >> tokenizer config file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-105/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 16:08:46,094 >> Special tokens file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-105/special_tokens_map.json\n",
+                        "{'loss': 0.2875, 'grad_norm': 0.5638000965118408, 'learning_rate': 8.665259359149132e-05, 'epoch': 0.63}\n",
+                        "{'loss': 0.2773, 'grad_norm': 0.8856341242790222, 'learning_rate': 8.491184090430364e-05, 'epoch': 0.65}\n",
+                        "{'loss': 0.2728, 'grad_norm': 0.933649480342865, 'learning_rate': 8.308429187984297e-05, 'epoch': 0.68}\n",
+                        "{'loss': 0.2676, 'grad_norm': 0.6383955478668213, 'learning_rate': 8.117449009293668e-05, 'epoch': 0.71}\n",
+                        "{'loss': 0.2793, 'grad_norm': 0.6104869246482849, 'learning_rate': 7.91871836117395e-05, 'epoch': 0.74}\n",
+                        "{'loss': 0.3009, 'grad_norm': 1.186869502067566, 'learning_rate': 7.712731319328798e-05, 'epoch': 0.77}\n",
+                        "{'loss': 0.2825, 'grad_norm': 0.4962313175201416, 'learning_rate': 7.500000000000001e-05, 'epoch': 0.8}\n",
+                        " 40%|████████████████▍                        | 140/350 [27:21<33:34,  9.59s/it][INFO|trainer.py:3819] 2024-09-21 16:14:20,188 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 16:14:20,188 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 16:14:20,188 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.2567569613456726, 'eval_runtime': 92.1163, 'eval_samples_per_second': 27.14, 'eval_steps_per_second': 27.14, 'epoch': 0.8}\n",
+                        " 40%|████████████████▍                        | 140/350 [28:53<33:34,  9.59s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 16:15:52,304 >> Saving model checkpoint to saves/Qwen2.5-1.5B-Instruct/checkpoint-140\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 16:15:54,027 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 16:15:54,027 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 1536,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 8960,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 12,\n",
+                        "  \"num_hidden_layers\": 28,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 16:15:54,069 >> tokenizer config file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-140/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 16:15:54,069 >> Special tokens file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-140/special_tokens_map.json\n",
+                        "{'loss': 0.2769, 'grad_norm': 0.8555291295051575, 'learning_rate': 7.281053286765815e-05, 'epoch': 0.82}\n",
+                        "{'loss': 0.2896, 'grad_norm': 0.9149414300918579, 'learning_rate': 7.056435515653059e-05, 'epoch': 0.85}\n",
+                        "{'loss': 0.2784, 'grad_norm': 0.47306105494499207, 'learning_rate': 6.826705121831976e-05, 'epoch': 0.88}\n",
+                        "{'loss': 0.2722, 'grad_norm': 0.5558005571365356, 'learning_rate': 6.592433251258423e-05, 'epoch': 0.91}\n",
+                        "{'loss': 0.2573, 'grad_norm': 1.440822958946228, 'learning_rate': 6.354202340715026e-05, 'epoch': 0.94}\n",
+                        "{'loss': 0.2766, 'grad_norm': 0.8847922086715698, 'learning_rate': 6.112604669781572e-05, 'epoch': 0.97}\n",
+                        "{'loss': 0.2693, 'grad_norm': 0.6979252099990845, 'learning_rate': 5.868240888334653e-05, 'epoch': 1.0}\n",
+                        " 50%|████████████████████▌                    | 175/350 [34:28<27:47,  9.53s/it][INFO|trainer.py:3819] 2024-09-21 16:21:27,237 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 16:21:27,237 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 16:21:27,237 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.2491111010313034, 'eval_runtime': 92.9559, 'eval_samples_per_second': 26.894, 'eval_steps_per_second': 26.894, 'epoch': 1.0}\n",
+                        " 50%|████████████████████▌                    | 175/350 [36:01<27:47,  9.53s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 16:23:00,193 >> Saving model checkpoint to saves/Qwen2.5-1.5B-Instruct/checkpoint-175\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 16:23:01,512 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 16:23:01,513 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 1536,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 8960,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 12,\n",
+                        "  \"num_hidden_layers\": 28,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 16:23:01,550 >> tokenizer config file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-175/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 16:23:01,550 >> Special tokens file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-175/special_tokens_map.json\n",
+                        "{'loss': 0.2619, 'grad_norm': 0.7065874934196472, 'learning_rate': 5.621718523237427e-05, 'epoch': 1.02}\n",
+                        "{'loss': 0.2496, 'grad_norm': 0.9854199886322021, 'learning_rate': 5.373650467932122e-05, 'epoch': 1.05}\n",
+                        "{'loss': 0.268, 'grad_norm': 1.2961649894714355, 'learning_rate': 5.124653458690365e-05, 'epoch': 1.08}\n",
+                        "{'loss': 0.2473, 'grad_norm': 0.6371685862541199, 'learning_rate': 4.875346541309637e-05, 'epoch': 1.11}\n",
+                        "{'loss': 0.2649, 'grad_norm': 0.5193257331848145, 'learning_rate': 4.626349532067879e-05, 'epoch': 1.14}\n",
+                        "{'loss': 0.2671, 'grad_norm': 0.5210095643997192, 'learning_rate': 4.378281476762576e-05, 'epoch': 1.17}\n",
+                        "{'loss': 0.2466, 'grad_norm': 0.6401721239089966, 'learning_rate': 4.131759111665349e-05, 'epoch': 1.19}\n",
+                        " 60%|████████████████████████▌                | 210/350 [41:35<22:11,  9.51s/it][INFO|trainer.py:3819] 2024-09-21 16:28:33,947 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 16:28:33,947 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 16:28:33,947 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.2544134855270386, 'eval_runtime': 94.0532, 'eval_samples_per_second': 26.581, 'eval_steps_per_second': 26.581, 'epoch': 1.19}\n",
+                        " 60%|████████████████████████▌                | 210/350 [43:09<22:11,  9.51s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 16:30:08,000 >> Saving model checkpoint to saves/Qwen2.5-1.5B-Instruct/checkpoint-210\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 16:30:09,340 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 16:30:09,341 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 1536,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 8960,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 12,\n",
+                        "  \"num_hidden_layers\": 28,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 16:30:09,379 >> tokenizer config file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-210/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 16:30:09,379 >> Special tokens file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-210/special_tokens_map.json\n",
+                        "{'loss': 0.2345, 'grad_norm': 0.5983948707580566, 'learning_rate': 3.887395330218429e-05, 'epoch': 1.22}\n",
+                        "{'loss': 0.2294, 'grad_norm': 0.8043653964996338, 'learning_rate': 3.6457976592849754e-05, 'epoch': 1.25}\n",
+                        "{'loss': 0.2518, 'grad_norm': 0.9972067475318909, 'learning_rate': 3.4075667487415785e-05, 'epoch': 1.28}\n",
+                        "{'loss': 0.2492, 'grad_norm': 0.8310278654098511, 'learning_rate': 3.173294878168025e-05, 'epoch': 1.31}\n",
+                        "{'loss': 0.2547, 'grad_norm': 0.6404473781585693, 'learning_rate': 2.9435644843469436e-05, 'epoch': 1.34}\n",
+                        "{'loss': 0.2495, 'grad_norm': 0.7588335871696472, 'learning_rate': 2.718946713234185e-05, 'epoch': 1.36}\n",
+                        "{'loss': 0.2733, 'grad_norm': 0.6872820854187012, 'learning_rate': 2.500000000000001e-05, 'epoch': 1.39}\n",
+                        " 70%|████████████████████████████▋            | 245/350 [48:44<16:51,  9.64s/it][INFO|trainer.py:3819] 2024-09-21 16:35:43,271 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 16:35:43,271 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 16:35:43,271 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.238626629114151, 'eval_runtime': 93.445, 'eval_samples_per_second': 26.754, 'eval_steps_per_second': 26.754, 'epoch': 1.39}\n",
+                        " 70%|████████████████████████████▋            | 245/350 [50:17<16:51,  9.64s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 16:37:16,717 >> Saving model checkpoint to saves/Qwen2.5-1.5B-Instruct/checkpoint-245\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 16:37:18,128 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 16:37:18,129 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 1536,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 8960,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 12,\n",
+                        "  \"num_hidden_layers\": 28,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 16:37:18,161 >> tokenizer config file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-245/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 16:37:18,161 >> Special tokens file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-245/special_tokens_map.json\n",
+                        "{'loss': 0.2567, 'grad_norm': 0.8496139645576477, 'learning_rate': 2.2872686806712035e-05, 'epoch': 1.42}\n",
+                        "{'loss': 0.2311, 'grad_norm': 0.6145327091217041, 'learning_rate': 2.0812816388260518e-05, 'epoch': 1.45}\n",
+                        "{'loss': 0.2171, 'grad_norm': 0.6917315721511841, 'learning_rate': 1.8825509907063327e-05, 'epoch': 1.48}\n",
+                        "{'loss': 0.2285, 'grad_norm': 0.8362339735031128, 'learning_rate': 1.691570812015704e-05, 'epoch': 1.51}\n",
+                        "{'loss': 0.2643, 'grad_norm': 0.8186646699905396, 'learning_rate': 1.5088159095696363e-05, 'epoch': 1.54}\n",
+                        "{'loss': 0.2331, 'grad_norm': 0.9536941051483154, 'learning_rate': 1.3347406408508695e-05, 'epoch': 1.56}\n",
+                        "{'loss': 0.2396, 'grad_norm': 0.5406892895698547, 'learning_rate': 1.1697777844051105e-05, 'epoch': 1.59}\n",
+                        " 80%|████████████████████████████████▊        | 280/350 [55:51<11:04,  9.49s/it][INFO|trainer.py:3819] 2024-09-21 16:42:50,749 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 16:42:50,749 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 16:42:50,749 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.23902197182178497, 'eval_runtime': 94.3044, 'eval_samples_per_second': 26.51, 'eval_steps_per_second': 26.51, 'epoch': 1.59}\n",
+                        " 80%|████████████████████████████████▊        | 280/350 [57:26<11:04,  9.49s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 16:44:25,054 >> Saving model checkpoint to saves/Qwen2.5-1.5B-Instruct/checkpoint-280\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 16:44:26,381 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 16:44:26,381 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 1536,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 8960,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 12,\n",
+                        "  \"num_hidden_layers\": 28,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 16:44:26,417 >> tokenizer config file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-280/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 16:44:26,417 >> Special tokens file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-280/special_tokens_map.json\n",
+                        "{'loss': 0.2464, 'grad_norm': 0.9152795076370239, 'learning_rate': 1.0143374638853891e-05, 'epoch': 1.62}\n",
+                        "{'loss': 0.2451, 'grad_norm': 0.6611983776092529, 'learning_rate': 8.688061284200266e-06, 'epoch': 1.65}\n",
+                        "{'loss': 0.2268, 'grad_norm': 0.6333246827125549, 'learning_rate': 7.33545591839222e-06, 'epoch': 1.68}\n",
+                        "{'loss': 0.2407, 'grad_norm': 0.6191487312316895, 'learning_rate': 6.088921331488568e-06, 'epoch': 1.71}\n",
+                        "{'loss': 0.2383, 'grad_norm': 0.8804998397827148, 'learning_rate': 4.951556604879048e-06, 'epoch': 1.73}\n",
+                        "{'loss': 0.2203, 'grad_norm': 0.7381444573402405, 'learning_rate': 3.9261894064796135e-06, 'epoch': 1.76}\n",
+                        "{'loss': 0.2373, 'grad_norm': 0.8267008066177368, 'learning_rate': 3.0153689607045845e-06, 'epoch': 1.79}\n",
+                        " 90%|███████████████████████████████████    | 315/350 [1:03:00<05:31,  9.47s/it][INFO|trainer.py:3819] 2024-09-21 16:49:59,378 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 16:49:59,378 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 16:49:59,378 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.24121001362800598, 'eval_runtime': 93.2566, 'eval_samples_per_second': 26.808, 'eval_steps_per_second': 26.808, 'epoch': 1.79}\n",
+                        " 90%|███████████████████████████████████    | 315/350 [1:04:33<05:31,  9.47s/it]\n",
+                        "100%|███████████████████████████████████████| 2500/2500 [01:33<00:00, 26.70it/s]\u001b[A\n",
+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 16:51:32,635 >> Saving model checkpoint to saves/Qwen2.5-1.5B-Instruct/checkpoint-315\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 16:51:33,921 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 16:51:33,921 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 1536,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 8960,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 12,\n",
+                        "  \"num_hidden_layers\": 28,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 16:51:33,959 >> tokenizer config file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-315/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 16:51:33,959 >> Special tokens file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-315/special_tokens_map.json\n",
+                        "{'loss': 0.2281, 'grad_norm': 0.8259851932525635, 'learning_rate': 2.221359710692961e-06, 'epoch': 1.82}\n",
+                        "{'loss': 0.2418, 'grad_norm': 0.7553776502609253, 'learning_rate': 1.5461356885461075e-06, 'epoch': 1.85}\n",
+                        "{'loss': 0.2474, 'grad_norm': 1.2472189664840698, 'learning_rate': 9.913756075728087e-07, 'epoch': 1.88}\n",
+                        "{'loss': 0.2323, 'grad_norm': 0.5642313957214355, 'learning_rate': 5.584586887435739e-07, 'epoch': 1.9}\n",
+                        "{'loss': 0.239, 'grad_norm': 0.6548100709915161, 'learning_rate': 2.4846123172992954e-07, 'epoch': 1.93}\n",
+                        "{'loss': 0.2458, 'grad_norm': 0.706020176410675, 'learning_rate': 6.215393905388278e-08, 'epoch': 1.96}\n",
+                        "{'loss': 0.2413, 'grad_norm': 0.7654218077659607, 'learning_rate': 0.0, 'epoch': 1.99}\n",
+                        "100%|███████████████████████████████████████| 350/350 [1:10:07<00:00,  9.51s/it][INFO|trainer.py:3819] 2024-09-21 16:57:06,607 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 16:57:06,607 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 16:57:06,607 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.23883095383644104, 'eval_runtime': 94.4427, 'eval_samples_per_second': 26.471, 'eval_steps_per_second': 26.471, 'epoch': 1.99}\n",
+                        "100%|███████████████████████████████████████| 350/350 [1:11:42<00:00,  9.51s/it]\n",
+                        "100%|███████████████████████████████████████| 2500/2500 [01:34<00:00, 27.16it/s]\u001b[A\n",
+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 16:58:41,050 >> Saving model checkpoint to saves/Qwen2.5-1.5B-Instruct/checkpoint-350\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 16:58:42,391 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 16:58:42,391 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 1536,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 8960,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 12,\n",
+                        "  \"num_hidden_layers\": 28,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 16:58:42,429 >> tokenizer config file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-350/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 16:58:42,429 >> Special tokens file saved in saves/Qwen2.5-1.5B-Instruct/checkpoint-350/special_tokens_map.json\n",
+                        "[INFO|trainer.py:2394] 2024-09-21 16:58:42,586 >> \n",
+                        "\n",
+                        "Training completed. Do not forget to share your model on huggingface.co/models =)\n",
+                        "\n",
+                        "\n",
+                        "{'train_runtime': 4303.7472, 'train_samples_per_second': 10.456, 'train_steps_per_second': 0.081, 'train_loss': 0.30218201875686646, 'epoch': 1.99}\n",
+                        "100%|███████████████████████████████████████| 350/350 [1:11:43<00:00, 12.30s/it]\n",
+                        "[INFO|trainer.py:3503] 2024-09-21 16:58:42,587 >> Saving model checkpoint to saves/Qwen2.5-1.5B-Instruct\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 16:58:43,138 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/5fee7c4ed634dc66c6e318c8ac2897b8b9154536/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 16:58:43,139 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 1536,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 8960,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 12,\n",
+                        "  \"num_hidden_layers\": 28,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 16:58:43,171 >> tokenizer config file saved in saves/Qwen2.5-1.5B-Instruct/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 16:58:43,171 >> Special tokens file saved in saves/Qwen2.5-1.5B-Instruct/special_tokens_map.json\n",
+                        "***** train metrics *****\n",
+                        "  epoch                    =        1.99\n",
+                        "  total_flos               = 161035698GF\n",
+                        "  train_loss               =      0.3022\n",
+                        "  train_runtime            =  1:11:43.74\n",
+                        "  train_samples_per_second =      10.456\n",
+                        "  train_steps_per_second   =       0.081\n",
+                        "Figure saved at: saves/Qwen2.5-1.5B-Instruct/training_loss.png\n",
+                        "Figure saved at: saves/Qwen2.5-1.5B-Instruct/training_eval_loss.png\n",
+                        "09/21/2024 16:58:43 - WARNING - llamafactory.extras.ploting - No metric eval_accuracy to plot.\n",
+                        "[INFO|trainer.py:3819] 2024-09-21 16:58:43,425 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 16:58:43,425 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 16:58:43,425 >>   Batch size = 1\n",
+                        "100%|███████████████████████████████████████| 2500/2500 [01:36<00:00, 26.04it/s]\n",
+                        "***** eval metrics *****\n",
+                        "  epoch                   =       1.99\n",
+                        "  eval_loss               =     0.2388\n",
+                        "  eval_runtime            = 0:01:36.10\n",
+                        "  eval_samples_per_second =     26.012\n",
+                        "  eval_steps_per_second   =     26.012\n",
+                        "[INFO|modelcard.py:449] 2024-09-21 17:00:19,534 >> Dropping the following result as it does not have all the necessary fields:\n",
+                        "{'task': {'name': 'Causal Language Modeling', 'type': 'text-generation'}}\n",
+                        "Current Directory:\n",
+                        "/home/inflaton/code/logical-reasoning/llama-factory\n",
+                        "loading env vars from: /home/inflaton/code/logical-reasoning/.env\n",
+                        "Adding /home/inflaton/code/logical-reasoning to sys.path\n",
+                        "loading /home/inflaton/code/logical-reasoning/llm_toolkit/logical_reasoning_utils.py\n",
+                        "Qwen Qwen2.5-0.5B-Instruct qwen config/mgtv_template.yaml ../datasets/mgtv\n",
+                        "Writing to config/models/Qwen2.5-0.5B-Instruct.yaml\n",
+                        "config/models/Qwen2.5-0.5B-Instruct.yaml:\n",
+                        " {\n",
+                        "  \"model_name_or_path\": \"Qwen/Qwen2.5-0.5B-Instruct\",\n",
+                        "  \"stage\": \"sft\",\n",
+                        "  \"do_train\": true,\n",
+                        "  \"finetuning_type\": \"lora\",\n",
+                        "  \"lora_target\": \"all\",\n",
+                        "  \"dataset\": \"alpaca_mgtv_p2\",\n",
+                        "  \"template\": \"qwen\",\n",
+                        "  \"cutoff_len\": 8192,\n",
+                        "  \"max_samples\": 25000,\n",
+                        "  \"overwrite_cache\": true,\n",
+                        "  \"preprocessing_num_workers\": 16,\n",
+                        "  \"output_dir\": \"saves/Qwen2.5-0.5B-Instruct\",\n",
+                        "  \"logging_steps\": 5,\n",
+                        "  \"save_steps\": 35,\n",
+                        "  \"plot_loss\": true,\n",
+                        "  \"per_device_train_batch_size\": 16,\n",
+                        "  \"gradient_accumulation_steps\": 8,\n",
+                        "  \"learning_rate\": 0.0001,\n",
+                        "  \"num_train_epochs\": 2.0,\n",
+                        "  \"lr_scheduler_type\": \"cosine\",\n",
+                        "  \"warmup_ratio\": 0.1,\n",
+                        "  \"bf16\": true,\n",
+                        "  \"ddp_timeout\": 180000000,\n",
+                        "  \"val_size\": 0.1,\n",
+                        "  \"per_device_eval_batch_size\": 1,\n",
+                        "  \"eval_strategy\": \"steps\",\n",
+                        "  \"eval_steps\": 35,\n",
+                        "  \"report_to\": \"none\",\n",
+                        "  \"run_name\": \"Qwen2.5-0.5B-Instruct_lora_sft\"\n",
+                        "}\n",
+                        "09/21/2024 17:00:25 - INFO - llamafactory.hparams.parser - Process rank: 0, device: cuda:0, n_gpu: 1, distributed training: False, compute dtype: torch.bfloat16\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 17:00:26,916 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 17:00:26,917 >> Model config Qwen2Config {\n",
+                        "  \"_name_or_path\": \"Qwen/Qwen2.5-0.5B-Instruct\",\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 896,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 4864,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 14,\n",
+                        "  \"num_hidden_layers\": 24,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 17:00:27,186 >> loading file vocab.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/vocab.json\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 17:00:27,186 >> loading file merges.txt from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/merges.txt\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 17:00:27,186 >> loading file tokenizer.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/tokenizer.json\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 17:00:27,186 >> loading file added_tokens.json from cache at None\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 17:00:27,186 >> loading file special_tokens_map.json from cache at None\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 17:00:27,186 >> loading file tokenizer_config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2533] 2024-09-21 17:00:27,298 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 17:00:28,386 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 17:00:28,386 >> Model config Qwen2Config {\n",
+                        "  \"_name_or_path\": \"Qwen/Qwen2.5-0.5B-Instruct\",\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 896,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 4864,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 14,\n",
+                        "  \"num_hidden_layers\": 24,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 17:00:28,652 >> loading file vocab.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/vocab.json\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 17:00:28,652 >> loading file merges.txt from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/merges.txt\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 17:00:28,652 >> loading file tokenizer.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/tokenizer.json\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 17:00:28,652 >> loading file added_tokens.json from cache at None\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 17:00:28,652 >> loading file special_tokens_map.json from cache at None\n",
+                        "[INFO|tokenization_utils_base.py:2289] 2024-09-21 17:00:28,652 >> loading file tokenizer_config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2533] 2024-09-21 17:00:28,744 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n",
+                        "09/21/2024 17:00:28 - INFO - llamafactory.data.template - Replace eos token: <|im_end|>\n",
+                        "09/21/2024 17:00:28 - INFO - llamafactory.data.loader - Loading dataset alpaca_mgtv_p2.json...\n",
+                        "Converting format of dataset (num_proc=16): 100%|█| 25000/25000 [00:00<00:00, 95\n",
+                        "Running tokenizer on dataset (num_proc=16): 100%|█| 25000/25000 [00:01<00:00, 15\n",
+                        "training example:\n",
+                        "input_ids:\n",
+                        "[151644, 8948, 198, 2610, 525, 264, 10950, 17847, 13, 151645, 198, 151644, 872, 198, 56568, 101909, 108024, 101497, 107969, 99329, 9370, 106040, 1773, 99329, 104190, 104506, 48443, 16, 13, 26853, 224, 57218, 28946, 36993, 101051, 46944, 107969, 27091, 3837, 107969, 27091, 36993, 53481, 46944, 100405, 99518, 104151, 101128, 9370, 57621, 8997, 17, 13, 89982, 68878, 17340, 99392, 107969, 99413, 3837, 107969, 99413, 20412, 107969, 27091, 111230, 8997, 18, 13, 26853, 224, 57218, 28946, 73670, 105396, 99885, 106386, 28330, 86119, 112469, 100246, 57621, 9370, 106538, 8997, 19, 13, 69162, 34204, 103991, 86119, 3837, 106040, 44063, 100345, 107591, 102104, 87752, 105220, 109487, 100653, 5122, 20412, 5373, 99520, 5373, 16530, 99335, 5373, 102104, 88991, 5373, 56007, 24339, 32100, 1773, 99200, 102104, 9370, 104317, 100142, 104506, 28311, 256, 481, 92498, 107969, 27091, 33108, 107969, 99413, 114562, 86119, 111230, 3837, 102104, 5122, 20412, 100631, 99520, 198, 256, 481, 92498, 107969, 27091, 33108, 107969, 99413, 53153, 101041, 100631, 108349, 83751, 63789, 20221, 86119, 111230, 3837, 102104, 5122, 16530, 99335, 198, 256, 481, 92498, 111842, 107666, 113479, 106386, 28330, 86119, 100631, 86119, 104151, 101128, 3837, 102104, 5122, 56007, 24339, 32100, 198, 256, 481, 92498, 111842, 107666, 99797, 108670, 34187, 107969, 99413, 106538, 3837, 102104, 5122, 102104, 88991, 198, 20, 13, 49602, 252, 99590, 15946, 53153, 42855, 99885, 102158, 27369, 3837, 105827, 65770, 99475, 109487, 101047, 110281, 18600, 1773, 77557, 3837, 108620, 99360, 2073, 99520, 854, 65770, 99475, 12857, 2073, 16530, 96332, 14880, 110439, 100001, 104190, 102104, 111842, 101080, 103936, 3407, 334, 107969, 27091, 66963, 73562, 109628, 45629, 105489, 3837, 104133, 111718, 106023, 5122, 101988, 115865, 110731, 9370, 105419, 3837, 115865, 99810, 69249, 59743, 104133, 104003, 115865, 36993, 16530, 101401, 68536, 99723, 3837, 115967, 104270, 102060, 110666, 112031, 1773, 14880, 109363, 115865, 110786, 101423, 104249, 3407, 334, 107969, 99413, 66963, 10236, 250, 253, 48921, 101221, 57218, 101961, 7948, 100894, 9370, 99288, 99818, 101063, 1773, 104269, 99288, 99818, 100774, 13343, 3837, 99798, 57218, 101961, 105664, 102373, 48921, 100271, 1773, 99650, 105616, 18493, 115865, 110731, 9370, 105419, 104388, 1773, 103968, 3837, 102606, 102115, 17340, 3837, 102373, 18493, 106340, 24562, 99774, 82224, 104424, 15946, 99372, 99244, 1773, 110597, 9370, 99288, 99818, 100012, 101416, 63109, 99242, 9370, 102373, 3837, 101988, 101938, 44063, 104003, 115865, 101329, 99314, 3837, 107974, 102373, 9370, 104575, 24562, 3837, 105699, 116418, 100005, 103000, 90663, 1773, 100147, 101070, 105443, 34187, 100097, 3837, 104989, 100833, 69249, 46944, 105190, 9370, 106023, 3407, 334, 111842, 101080, 103936, 66963, 4891, 223, 115, 100623, 21317, 99315, 101037, 198, 151645, 198, 151644, 77091, 198, 99520, 151645]\n",
+                        "inputs:\n",
+                        "<|im_start|>system\n",
+                        "You are a helpful assistant.<|im_end|>\n",
+                        "<|im_start|>user\n",
+                        "你是一个情景猜谜游戏的主持人。游戏规则如下：\n",
+                        "\n",
+                        "1. 参与者会得到一个谜面，谜面会描述一个简单又难以理解的事件。\n",
+                        "2. 主持人知道谜底，谜底是谜面的答案。\n",
+                        "3. 参与者可以询问任何封闭式问题来找寻事件的真相。\n",
+                        "4. 对于每个问题，主持人将根据实际情况回答以下五个选项之一：是、不是、不重要、回答正确、问法错误。各回答的判断标准如下：\n",
+                        "   - 若谜面和谜底能找到问题的答案，回答：是或者不是\n",
+                        "   - 若谜面和谜底不能直接或者间接推断出问题的答案，回答：不重要\n",
+                        "   - 若参与者提问不是一个封闭式问题或者问题难以理解，回答：问法错误\n",
+                        "   - 若参与者提问基本还原了谜底真相，回答：回答正确\n",
+                        "5. 回答中不能添加任何其它信息，也不能省略选项中的任何一个字。例如，不可以把“不是”省略成“不”。\n",
+                        "\n",
+                        "请严格按照这些规则回答参与者提出的问题。\n",
+                        "\n",
+                        "**谜面:** 在甄家村里，有一个古老的传说：每年南瓜丰收的季节，南瓜田里总有一个最大的南瓜会不翼而飞，村民们对此现象困惑不解。请找出南瓜失踪背后的原因。\n",
+                        "\n",
+                        "**谜底:** 真相原来与一位年迈的农夫有关。这位农夫年轻时，曾与一位美丽的姑娘相恋。他们约定在南瓜丰收的季节结婚。然而，命运弄人，姑娘在婚礼前的一场意外中离世。悲伤的农夫为了纪念心爱的姑娘，每年都会将最大的南瓜偷走，放到姑娘的墓前，以此寄托自己的哀思。这一行为延续了多年，成为了乡村里一个神秘的传说。\n",
+                        "\n",
+                        "**参与者提出的问题:** 偷的人信神吗\n",
+                        "<|im_end|>\n",
+                        "<|im_start|>assistant\n",
+                        "不是<|im_end|>\n",
+                        "label_ids:\n",
+                        "[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 99520, 151645]\n",
+                        "labels:\n",
+                        "不是<|im_end|>\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 17:00:32,420 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 17:00:32,420 >> Model config Qwen2Config {\n",
+                        "  \"_name_or_path\": \"Qwen/Qwen2.5-0.5B-Instruct\",\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 896,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 4864,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 14,\n",
+                        "  \"num_hidden_layers\": 24,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|modeling_utils.py:3634] 2024-09-21 17:00:32,432 >> loading weights file model.safetensors from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/model.safetensors\n",
+                        "[INFO|modeling_utils.py:1572] 2024-09-21 17:00:32,436 >> Instantiating Qwen2ForCausalLM model under default dtype torch.bfloat16.\n",
+                        "[INFO|configuration_utils.py:1038] 2024-09-21 17:00:32,437 >> Generate config GenerationConfig {\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|modeling_utils.py:4463] 2024-09-21 17:00:58,518 >> All model checkpoint weights were used when initializing Qwen2ForCausalLM.\n",
+                        "\n",
+                        "[INFO|modeling_utils.py:4471] 2024-09-21 17:00:58,518 >> All the weights of Qwen2ForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-0.5B-Instruct.\n",
+                        "If your task is similar to the task the model of the checkpoint was trained on, you can already use Qwen2ForCausalLM for predictions without further training.\n",
+                        "[INFO|configuration_utils.py:993] 2024-09-21 17:00:58,782 >> loading configuration file generation_config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/generation_config.json\n",
+                        "[INFO|configuration_utils.py:1038] 2024-09-21 17:00:58,782 >> Generate config GenerationConfig {\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"do_sample\": true,\n",
+                        "  \"eos_token_id\": [\n",
+                        "    151645,\n",
+                        "    151643\n",
+                        "  ],\n",
+                        "  \"pad_token_id\": 151643,\n",
+                        "  \"repetition_penalty\": 1.1,\n",
+                        "  \"temperature\": 0.7,\n",
+                        "  \"top_k\": 20,\n",
+                        "  \"top_p\": 0.8\n",
+                        "}\n",
+                        "\n",
+                        "09/21/2024 17:00:58 - INFO - llamafactory.model.model_utils.checkpointing - Gradient checkpointing enabled.\n",
+                        "09/21/2024 17:00:58 - INFO - llamafactory.model.model_utils.attention - Using torch SDPA for faster training and inference.\n",
+                        "09/21/2024 17:00:58 - INFO - llamafactory.model.adapter - Upcasting trainable params to float32.\n",
+                        "09/21/2024 17:00:58 - INFO - llamafactory.model.adapter - Fine-tuning method: LoRA\n",
+                        "09/21/2024 17:00:58 - INFO - llamafactory.model.model_utils.misc - Found linear modules: gate_proj,up_proj,k_proj,o_proj,q_proj,v_proj,down_proj\n",
+                        "09/21/2024 17:00:59 - INFO - llamafactory.model.loader - trainable params: 4,399,104 || all params: 498,431,872 || trainable%: 0.8826\n",
+                        "[INFO|trainer.py:648] 2024-09-21 17:00:59,124 >> Using auto half precision backend\n",
+                        "[INFO|trainer.py:2134] 2024-09-21 17:00:59,440 >> ***** Running training *****\n",
+                        "[INFO|trainer.py:2135] 2024-09-21 17:00:59,440 >>   Num examples = 22,500\n",
+                        "[INFO|trainer.py:2136] 2024-09-21 17:00:59,440 >>   Num Epochs = 2\n",
+                        "[INFO|trainer.py:2137] 2024-09-21 17:00:59,440 >>   Instantaneous batch size per device = 16\n",
+                        "[INFO|trainer.py:2140] 2024-09-21 17:00:59,440 >>   Total train batch size (w. parallel, distributed & accumulation) = 128\n",
+                        "[INFO|trainer.py:2141] 2024-09-21 17:00:59,440 >>   Gradient Accumulation steps = 8\n",
+                        "[INFO|trainer.py:2142] 2024-09-21 17:00:59,440 >>   Total optimization steps = 350\n",
+                        "[INFO|trainer.py:2143] 2024-09-21 17:00:59,441 >>   Number of trainable parameters = 4,399,104\n",
+                        "{'loss': 1.1184, 'grad_norm': 15.737517356872559, 'learning_rate': 1.4285714285714285e-05, 'epoch': 0.03}\n",
+                        "{'loss': 0.9305, 'grad_norm': 7.921570777893066, 'learning_rate': 2.857142857142857e-05, 'epoch': 0.06}\n",
+                        "{'loss': 0.6076, 'grad_norm': 3.3468737602233887, 'learning_rate': 4.2857142857142856e-05, 'epoch': 0.09}\n",
+                        "{'loss': 0.5437, 'grad_norm': 2.368464708328247, 'learning_rate': 5.714285714285714e-05, 'epoch': 0.11}\n",
+                        "{'loss': 0.5106, 'grad_norm': 3.843911647796631, 'learning_rate': 7.142857142857143e-05, 'epoch': 0.14}\n",
+                        "{'loss': 0.4692, 'grad_norm': 1.8563235998153687, 'learning_rate': 8.571428571428571e-05, 'epoch': 0.17}\n",
+                        "{'loss': 0.4381, 'grad_norm': 1.487918496131897, 'learning_rate': 0.0001, 'epoch': 0.2}\n",
+                        " 10%|████▏                                     | 35/350 [02:29<22:10,  4.22s/it][INFO|trainer.py:3819] 2024-09-21 17:03:28,974 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 17:03:28,974 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 17:03:28,974 >>   Batch size = 1\n",
+                        "\n",
+                        "  0%|                                                  | 0/2500 [00:00<?, ?it/s]\u001b[A\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.3907283544540405, 'eval_runtime': 83.0912, 'eval_samples_per_second': 30.087, 'eval_steps_per_second': 30.087, 'epoch': 0.2}\n",
+                        " 10%|████▏                                     | 35/350 [03:52<22:10,  4.22s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 17:04:52,065 >> Saving model checkpoint to saves/Qwen2.5-0.5B-Instruct/checkpoint-35\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 17:04:52,623 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 17:04:52,623 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 896,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 4864,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 14,\n",
+                        "  \"num_hidden_layers\": 24,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 17:04:52,647 >> tokenizer config file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-35/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 17:04:52,647 >> Special tokens file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-35/special_tokens_map.json\n",
+                        "{'loss': 0.4104, 'grad_norm': 2.7992444038391113, 'learning_rate': 9.993784606094612e-05, 'epoch': 0.23}\n",
+                        "{'loss': 0.3919, 'grad_norm': 1.2948148250579834, 'learning_rate': 9.975153876827008e-05, 'epoch': 0.26}\n",
+                        "{'loss': 0.3958, 'grad_norm': 2.0029242038726807, 'learning_rate': 9.944154131125642e-05, 'epoch': 0.28}\n",
+                        "{'loss': 0.3703, 'grad_norm': 1.9004690647125244, 'learning_rate': 9.900862439242719e-05, 'epoch': 0.31}\n",
+                        "{'loss': 0.3837, 'grad_norm': 2.839643716812134, 'learning_rate': 9.84538643114539e-05, 'epoch': 0.34}\n",
+                        "{'loss': 0.3435, 'grad_norm': 1.7279853820800781, 'learning_rate': 9.777864028930705e-05, 'epoch': 0.37}\n",
+                        "{'loss': 0.3556, 'grad_norm': 1.0835622549057007, 'learning_rate': 9.698463103929542e-05, 'epoch': 0.4}\n",
+                        " 20%|████████▍                                 | 70/350 [06:21<19:49,  4.25s/it][INFO|trainer.py:3819] 2024-09-21 17:07:21,360 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 17:07:21,360 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 17:07:21,360 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.3123813569545746, 'eval_runtime': 81.7215, 'eval_samples_per_second': 30.592, 'eval_steps_per_second': 30.592, 'epoch': 0.4}\n",
+                        " 20%|████████▍                                 | 70/350 [07:43<19:49,  4.25s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 17:08:43,082 >> Saving model checkpoint to saves/Qwen2.5-0.5B-Instruct/checkpoint-70\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 17:08:43,882 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 17:08:43,882 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 896,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 4864,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 14,\n",
+                        "  \"num_hidden_layers\": 24,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 17:08:43,903 >> tokenizer config file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-70/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 17:08:43,903 >> Special tokens file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-70/special_tokens_map.json\n",
+                        "{'loss': 0.3216, 'grad_norm': 1.249293565750122, 'learning_rate': 9.607381059352038e-05, 'epoch': 0.43}\n",
+                        "{'loss': 0.3061, 'grad_norm': 1.9808311462402344, 'learning_rate': 9.504844339512095e-05, 'epoch': 0.45}\n",
+                        "{'loss': 0.3325, 'grad_norm': 2.327874183654785, 'learning_rate': 9.391107866851143e-05, 'epoch': 0.48}\n",
+                        "{'loss': 0.332, 'grad_norm': 2.0999391078948975, 'learning_rate': 9.266454408160779e-05, 'epoch': 0.51}\n",
+                        "{'loss': 0.3349, 'grad_norm': 2.11915922164917, 'learning_rate': 9.131193871579975e-05, 'epoch': 0.54}\n",
+                        "{'loss': 0.3162, 'grad_norm': 1.733162760734558, 'learning_rate': 8.985662536114613e-05, 'epoch': 0.57}\n",
+                        "{'loss': 0.3228, 'grad_norm': 1.1676844358444214, 'learning_rate': 8.83022221559489e-05, 'epoch': 0.6}\n",
+                        " 30%|████████████▎                            | 105/350 [10:13<17:14,  4.22s/it][INFO|trainer.py:3819] 2024-09-21 17:11:12,460 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 17:11:12,460 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 17:11:12,460 >>   Batch size = 1\n",
+                        "\n",
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+                        " 78%|██████████████████████████████▌        | 1960/2500 [01:03<00:17, 30.29it/s]\u001b[A\n",
+                        " 79%|██████████████████████████████▋        | 1964/2500 [01:04<00:17, 30.40it/s]\u001b[A\n",
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+                        " 81%|███████████████████████████████▍       | 2016/2500 [01:05<00:15, 31.55it/s]\u001b[A\n",
+                        " 81%|███████████████████████████████▌       | 2020/2500 [01:05<00:16, 29.86it/s]\u001b[A\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.33586153388023376, 'eval_runtime': 81.7139, 'eval_samples_per_second': 30.595, 'eval_steps_per_second': 30.595, 'epoch': 0.6}\n",
+                        " 30%|████████████▎                            | 105/350 [11:34<17:14,  4.22s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 17:12:34,174 >> Saving model checkpoint to saves/Qwen2.5-0.5B-Instruct/checkpoint-105\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 17:12:34,739 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 17:12:34,739 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 896,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 4864,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 14,\n",
+                        "  \"num_hidden_layers\": 24,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 17:12:34,760 >> tokenizer config file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-105/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 17:12:34,760 >> Special tokens file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-105/special_tokens_map.json\n",
+                        "{'loss': 0.3165, 'grad_norm': 1.040158748626709, 'learning_rate': 8.665259359149132e-05, 'epoch': 0.63}\n",
+                        "{'loss': 0.3019, 'grad_norm': 1.2740882635116577, 'learning_rate': 8.491184090430364e-05, 'epoch': 0.65}\n",
+                        "{'loss': 0.3119, 'grad_norm': 1.2684509754180908, 'learning_rate': 8.308429187984297e-05, 'epoch': 0.68}\n",
+                        "{'loss': 0.2917, 'grad_norm': 1.1115374565124512, 'learning_rate': 8.117449009293668e-05, 'epoch': 0.71}\n",
+                        "{'loss': 0.2885, 'grad_norm': 1.1410064697265625, 'learning_rate': 7.91871836117395e-05, 'epoch': 0.74}\n",
+                        "{'loss': 0.3216, 'grad_norm': 2.9339027404785156, 'learning_rate': 7.712731319328798e-05, 'epoch': 0.77}\n",
+                        "{'loss': 0.3026, 'grad_norm': 1.4184118509292603, 'learning_rate': 7.500000000000001e-05, 'epoch': 0.8}\n",
+                        " 40%|████████████████▍                        | 140/350 [14:04<14:55,  4.26s/it][INFO|trainer.py:3819] 2024-09-21 17:15:04,041 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 17:15:04,041 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 17:15:04,041 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.2879035770893097, 'eval_runtime': 82.6814, 'eval_samples_per_second': 30.237, 'eval_steps_per_second': 30.237, 'epoch': 0.8}\n",
+                        " 40%|████████████████▍                        | 140/350 [15:27<14:55,  4.26s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 17:16:26,723 >> Saving model checkpoint to saves/Qwen2.5-0.5B-Instruct/checkpoint-140\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 17:16:27,259 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 17:16:27,260 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 896,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 4864,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 14,\n",
+                        "  \"num_hidden_layers\": 24,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 17:16:27,281 >> tokenizer config file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-140/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 17:16:27,281 >> Special tokens file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-140/special_tokens_map.json\n",
+                        "{'loss': 0.2798, 'grad_norm': 1.3493735790252686, 'learning_rate': 7.281053286765815e-05, 'epoch': 0.82}\n",
+                        "{'loss': 0.3084, 'grad_norm': 1.1956149339675903, 'learning_rate': 7.056435515653059e-05, 'epoch': 0.85}\n",
+                        "{'loss': 0.2996, 'grad_norm': 1.1371078491210938, 'learning_rate': 6.826705121831976e-05, 'epoch': 0.88}\n",
+                        "{'loss': 0.2936, 'grad_norm': 1.1137551069259644, 'learning_rate': 6.592433251258423e-05, 'epoch': 0.91}\n",
+                        "{'loss': 0.2718, 'grad_norm': 2.9275758266448975, 'learning_rate': 6.354202340715026e-05, 'epoch': 0.94}\n",
+                        "{'loss': 0.3136, 'grad_norm': 2.6529040336608887, 'learning_rate': 6.112604669781572e-05, 'epoch': 0.97}\n",
+                        "{'loss': 0.2802, 'grad_norm': 1.0029186010360718, 'learning_rate': 5.868240888334653e-05, 'epoch': 1.0}\n",
+                        " 50%|████████████████████▌                    | 175/350 [17:56<12:23,  4.25s/it][INFO|trainer.py:3819] 2024-09-21 17:18:55,953 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 17:18:55,953 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 17:18:55,953 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.2749469578266144, 'eval_runtime': 81.1488, 'eval_samples_per_second': 30.808, 'eval_steps_per_second': 30.808, 'epoch': 1.0}\n",
+                        " 50%|████████████████████▌                    | 175/350 [19:17<12:23,  4.25s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 17:20:17,103 >> Saving model checkpoint to saves/Qwen2.5-0.5B-Instruct/checkpoint-175\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 17:20:17,688 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 17:20:17,689 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 896,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 4864,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 14,\n",
+                        "  \"num_hidden_layers\": 24,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 17:20:17,710 >> tokenizer config file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-175/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 17:20:17,710 >> Special tokens file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-175/special_tokens_map.json\n",
+                        "{'loss': 0.2674, 'grad_norm': 1.5481024980545044, 'learning_rate': 5.621718523237427e-05, 'epoch': 1.02}\n",
+                        "{'loss': 0.2629, 'grad_norm': 1.1264318227767944, 'learning_rate': 5.373650467932122e-05, 'epoch': 1.05}\n",
+                        "{'loss': 0.2732, 'grad_norm': 1.3646587133407593, 'learning_rate': 5.124653458690365e-05, 'epoch': 1.08}\n",
+                        "{'loss': 0.271, 'grad_norm': 0.825769305229187, 'learning_rate': 4.875346541309637e-05, 'epoch': 1.11}\n",
+                        "{'loss': 0.2714, 'grad_norm': 0.9982427954673767, 'learning_rate': 4.626349532067879e-05, 'epoch': 1.14}\n",
+                        "{'loss': 0.2962, 'grad_norm': 2.239053964614868, 'learning_rate': 4.378281476762576e-05, 'epoch': 1.17}\n",
+                        "{'loss': 0.2645, 'grad_norm': 0.8168760538101196, 'learning_rate': 4.131759111665349e-05, 'epoch': 1.19}\n",
+                        " 60%|████████████████████████▌                | 210/350 [21:46<09:53,  4.24s/it][INFO|trainer.py:3819] 2024-09-21 17:22:46,303 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 17:22:46,303 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 17:22:46,303 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.2682396173477173, 'eval_runtime': 80.9181, 'eval_samples_per_second': 30.895, 'eval_steps_per_second': 30.895, 'epoch': 1.19}\n",
+                        " 60%|████████████████████████▌                | 210/350 [23:07<09:53,  4.24s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 17:24:07,222 >> Saving model checkpoint to saves/Qwen2.5-0.5B-Instruct/checkpoint-210\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 17:24:07,801 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 17:24:07,801 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 896,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 4864,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 14,\n",
+                        "  \"num_hidden_layers\": 24,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 17:24:07,827 >> tokenizer config file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-210/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 17:24:07,827 >> Special tokens file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-210/special_tokens_map.json\n",
+                        "{'loss': 0.2621, 'grad_norm': 1.397253155708313, 'learning_rate': 3.887395330218429e-05, 'epoch': 1.22}\n",
+                        "{'loss': 0.2458, 'grad_norm': 1.1573820114135742, 'learning_rate': 3.6457976592849754e-05, 'epoch': 1.25}\n",
+                        "{'loss': 0.2651, 'grad_norm': 2.0793874263763428, 'learning_rate': 3.4075667487415785e-05, 'epoch': 1.28}\n",
+                        "{'loss': 0.2654, 'grad_norm': 1.2757207155227661, 'learning_rate': 3.173294878168025e-05, 'epoch': 1.31}\n",
+                        "{'loss': 0.263, 'grad_norm': 1.1064047813415527, 'learning_rate': 2.9435644843469436e-05, 'epoch': 1.34}\n",
+                        "{'loss': 0.2776, 'grad_norm': 1.7825045585632324, 'learning_rate': 2.718946713234185e-05, 'epoch': 1.36}\n",
+                        "{'loss': 0.3012, 'grad_norm': 1.2948428392410278, 'learning_rate': 2.500000000000001e-05, 'epoch': 1.39}\n",
+                        " 70%|████████████████████████████▋            | 245/350 [25:37<07:31,  4.30s/it][INFO|trainer.py:3819] 2024-09-21 17:26:36,677 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 17:26:36,678 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 17:26:36,678 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.25933218002319336, 'eval_runtime': 80.6125, 'eval_samples_per_second': 31.013, 'eval_steps_per_second': 31.013, 'epoch': 1.39}\n",
+                        " 70%|████████████████████████████▋            | 245/350 [26:57<07:31,  4.30s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 17:27:57,291 >> Saving model checkpoint to saves/Qwen2.5-0.5B-Instruct/checkpoint-245\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 17:27:57,841 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 17:27:57,841 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 896,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 4864,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 14,\n",
+                        "  \"num_hidden_layers\": 24,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 17:27:57,863 >> tokenizer config file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-245/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 17:27:57,863 >> Special tokens file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-245/special_tokens_map.json\n",
+                        "{'loss': 0.2677, 'grad_norm': 1.3902900218963623, 'learning_rate': 2.2872686806712035e-05, 'epoch': 1.42}\n",
+                        "{'loss': 0.2483, 'grad_norm': 1.1757906675338745, 'learning_rate': 2.0812816388260518e-05, 'epoch': 1.45}\n",
+                        "{'loss': 0.2406, 'grad_norm': 1.2844176292419434, 'learning_rate': 1.8825509907063327e-05, 'epoch': 1.48}\n",
+                        "{'loss': 0.2531, 'grad_norm': 1.3673418760299683, 'learning_rate': 1.691570812015704e-05, 'epoch': 1.51}\n",
+                        "{'loss': 0.2702, 'grad_norm': 1.176766276359558, 'learning_rate': 1.5088159095696363e-05, 'epoch': 1.54}\n",
+                        "{'loss': 0.255, 'grad_norm': 1.8224906921386719, 'learning_rate': 1.3347406408508695e-05, 'epoch': 1.56}\n",
+                        "{'loss': 0.2628, 'grad_norm': 1.1993753910064697, 'learning_rate': 1.1697777844051105e-05, 'epoch': 1.59}\n",
+                        " 80%|████████████████████████████████▊        | 280/350 [29:27<04:56,  4.24s/it][INFO|trainer.py:3819] 2024-09-21 17:30:26,762 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 17:30:26,762 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 17:30:26,762 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.2647002041339874, 'eval_runtime': 80.562, 'eval_samples_per_second': 31.032, 'eval_steps_per_second': 31.032, 'epoch': 1.59}\n",
+                        " 80%|████████████████████████████████▊        | 280/350 [30:47<04:56,  4.24s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 17:31:47,325 >> Saving model checkpoint to saves/Qwen2.5-0.5B-Instruct/checkpoint-280\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 17:31:47,861 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 17:31:47,861 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 896,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 4864,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 14,\n",
+                        "  \"num_hidden_layers\": 24,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 17:31:47,885 >> tokenizer config file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-280/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 17:31:47,885 >> Special tokens file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-280/special_tokens_map.json\n",
+                        "{'loss': 0.2624, 'grad_norm': 1.6778804063796997, 'learning_rate': 1.0143374638853891e-05, 'epoch': 1.62}\n",
+                        "{'loss': 0.2604, 'grad_norm': 1.305879831314087, 'learning_rate': 8.688061284200266e-06, 'epoch': 1.65}\n",
+                        "{'loss': 0.234, 'grad_norm': 1.0664318799972534, 'learning_rate': 7.33545591839222e-06, 'epoch': 1.68}\n",
+                        "{'loss': 0.2584, 'grad_norm': 1.422717571258545, 'learning_rate': 6.088921331488568e-06, 'epoch': 1.71}\n",
+                        "{'loss': 0.2521, 'grad_norm': 1.3670940399169922, 'learning_rate': 4.951556604879048e-06, 'epoch': 1.73}\n",
+                        "{'loss': 0.2412, 'grad_norm': 1.36295747756958, 'learning_rate': 3.9261894064796135e-06, 'epoch': 1.76}\n",
+                        "{'loss': 0.2493, 'grad_norm': 1.4943523406982422, 'learning_rate': 3.0153689607045845e-06, 'epoch': 1.79}\n",
+                        " 90%|████████████████████████████████████▉    | 315/350 [33:17<02:29,  4.26s/it][INFO|trainer.py:3819] 2024-09-21 17:34:16,745 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 17:34:16,745 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 17:34:16,745 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.26533499360084534, 'eval_runtime': 80.2429, 'eval_samples_per_second': 31.155, 'eval_steps_per_second': 31.155, 'epoch': 1.79}\n",
+                        " 90%|████████████████████████████████████▉    | 315/350 [34:37<02:29,  4.26s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 17:35:36,988 >> Saving model checkpoint to saves/Qwen2.5-0.5B-Instruct/checkpoint-315\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 17:35:37,535 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 17:35:37,536 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 896,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 4864,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 14,\n",
+                        "  \"num_hidden_layers\": 24,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 17:35:37,562 >> tokenizer config file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-315/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 17:35:37,562 >> Special tokens file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-315/special_tokens_map.json\n",
+                        "{'loss': 0.2384, 'grad_norm': 1.4463350772857666, 'learning_rate': 2.221359710692961e-06, 'epoch': 1.82}\n",
+                        "{'loss': 0.2504, 'grad_norm': 1.4378561973571777, 'learning_rate': 1.5461356885461075e-06, 'epoch': 1.85}\n",
+                        "{'loss': 0.2644, 'grad_norm': 2.302417278289795, 'learning_rate': 9.913756075728087e-07, 'epoch': 1.88}\n",
+                        "{'loss': 0.2634, 'grad_norm': 1.0203107595443726, 'learning_rate': 5.584586887435739e-07, 'epoch': 1.9}\n",
+                        "{'loss': 0.2678, 'grad_norm': 1.4266246557235718, 'learning_rate': 2.4846123172992954e-07, 'epoch': 1.93}\n",
+                        "{'loss': 0.2724, 'grad_norm': 1.2000150680541992, 'learning_rate': 6.215393905388278e-08, 'epoch': 1.96}\n",
+                        "{'loss': 0.2642, 'grad_norm': 1.3346699476242065, 'learning_rate': 0.0, 'epoch': 1.99}\n",
+                        "100%|█████████████████████████████████████████| 350/350 [37:04<00:00,  4.17s/it][INFO|trainer.py:3819] 2024-09-21 17:38:04,120 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 17:38:04,120 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 17:38:04,120 >>   Batch size = 1\n",
+                        "\n",
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+                        "                                                                                \u001b[A\n",
+                        "\u001b[A{'eval_loss': 0.26338472962379456, 'eval_runtime': 79.5162, 'eval_samples_per_second': 31.44, 'eval_steps_per_second': 31.44, 'epoch': 1.99}\n",
+                        "100%|█████████████████████████████████████████| 350/350 [38:24<00:00,  4.17s/it]\n",
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+                        "                                                                                \u001b[A[INFO|trainer.py:3503] 2024-09-21 17:39:23,636 >> Saving model checkpoint to saves/Qwen2.5-0.5B-Instruct/checkpoint-350\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 17:39:24,176 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 17:39:24,176 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 896,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 4864,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 14,\n",
+                        "  \"num_hidden_layers\": 24,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 17:39:24,198 >> tokenizer config file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-350/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 17:39:24,198 >> Special tokens file saved in saves/Qwen2.5-0.5B-Instruct/checkpoint-350/special_tokens_map.json\n",
+                        "[INFO|trainer.py:2394] 2024-09-21 17:39:24,314 >> \n",
+                        "\n",
+                        "Training completed. Do not forget to share your model on huggingface.co/models =)\n",
+                        "\n",
+                        "\n",
+                        "{'train_runtime': 2304.8725, 'train_samples_per_second': 19.524, 'train_steps_per_second': 0.152, 'train_loss': 0.32685707432883127, 'epoch': 1.99}\n",
+                        "100%|█████████████████████████████████████████| 350/350 [38:24<00:00,  6.59s/it]\n",
+                        "[INFO|trainer.py:3503] 2024-09-21 17:39:24,314 >> Saving model checkpoint to saves/Qwen2.5-0.5B-Instruct\n",
+                        "[INFO|configuration_utils.py:733] 2024-09-21 17:39:24,851 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--Qwen--Qwen2.5-0.5B-Instruct/snapshots/a8b602d9dafd3a75d382e62757d83d89fca3be54/config.json\n",
+                        "[INFO|configuration_utils.py:800] 2024-09-21 17:39:24,851 >> Model config Qwen2Config {\n",
+                        "  \"architectures\": [\n",
+                        "    \"Qwen2ForCausalLM\"\n",
+                        "  ],\n",
+                        "  \"attention_dropout\": 0.0,\n",
+                        "  \"bos_token_id\": 151643,\n",
+                        "  \"eos_token_id\": 151645,\n",
+                        "  \"hidden_act\": \"silu\",\n",
+                        "  \"hidden_size\": 896,\n",
+                        "  \"initializer_range\": 0.02,\n",
+                        "  \"intermediate_size\": 4864,\n",
+                        "  \"max_position_embeddings\": 32768,\n",
+                        "  \"max_window_layers\": 21,\n",
+                        "  \"model_type\": \"qwen2\",\n",
+                        "  \"num_attention_heads\": 14,\n",
+                        "  \"num_hidden_layers\": 24,\n",
+                        "  \"num_key_value_heads\": 2,\n",
+                        "  \"rms_norm_eps\": 1e-06,\n",
+                        "  \"rope_theta\": 1000000.0,\n",
+                        "  \"sliding_window\": null,\n",
+                        "  \"tie_word_embeddings\": true,\n",
+                        "  \"torch_dtype\": \"bfloat16\",\n",
+                        "  \"transformers_version\": \"4.43.3\",\n",
+                        "  \"use_cache\": true,\n",
+                        "  \"use_sliding_window\": false,\n",
+                        "  \"vocab_size\": 151936\n",
+                        "}\n",
+                        "\n",
+                        "[INFO|tokenization_utils_base.py:2702] 2024-09-21 17:39:24,873 >> tokenizer config file saved in saves/Qwen2.5-0.5B-Instruct/tokenizer_config.json\n",
+                        "[INFO|tokenization_utils_base.py:2711] 2024-09-21 17:39:24,873 >> Special tokens file saved in saves/Qwen2.5-0.5B-Instruct/special_tokens_map.json\n",
+                        "***** train metrics *****\n",
+                        "  epoch                    =       1.99\n",
+                        "  total_flos               = 44213382GF\n",
+                        "  train_loss               =     0.3269\n",
+                        "  train_runtime            = 0:38:24.87\n",
+                        "  train_samples_per_second =     19.524\n",
+                        "  train_steps_per_second   =      0.152\n",
+                        "Figure saved at: saves/Qwen2.5-0.5B-Instruct/training_loss.png\n",
+                        "Figure saved at: saves/Qwen2.5-0.5B-Instruct/training_eval_loss.png\n",
+                        "09/21/2024 17:39:25 - WARNING - llamafactory.extras.ploting - No metric eval_accuracy to plot.\n",
+                        "[INFO|trainer.py:3819] 2024-09-21 17:39:25,047 >> \n",
+                        "***** Running Evaluation *****\n",
+                        "[INFO|trainer.py:3821] 2024-09-21 17:39:25,048 >>   Num examples = 2500\n",
+                        "[INFO|trainer.py:3824] 2024-09-21 17:39:25,048 >>   Batch size = 1\n",
+                        "100%|███████████████████████████████████████| 2500/2500 [01:18<00:00, 31.98it/s]\n",
+                        "***** eval metrics *****\n",
+                        "  epoch                   =       1.99\n",
+                        "  eval_loss               =     0.2634\n",
+                        "  eval_runtime            = 0:01:18.20\n",
+                        "  eval_samples_per_second =     31.968\n",
+                        "  eval_steps_per_second   =     31.968\n",
+                        "[INFO|modelcard.py:449] 2024-09-21 17:40:43,252 >> Dropping the following result as it does not have all the necessary fields:\n",
+                        "{'task': {'name': 'Causal Language Modeling', 'type': 'text-generation'}}\n",
+                        "CPU times: user 44.7 s, sys: 20.2 s, total: 1min 4s\n",
+                        "Wall time: 1h 55min 33s\n"
+                    ]
+                }
+            ],
+            "source": [
+                "%%time\n",
+                "\n",
+                "!./scripts/tune-mgtv-bf16.sh"
+            ]
+        }
+    ],
+    "metadata": {
+        "accelerator": "GPU",
+        "application/vnd.databricks.v1+notebook": {
+            "dashboards": [],
+            "environmentMetadata": null,
+            "language": "python",
+            "notebookMetadata": {
+                "pythonIndentUnit": 4
+            },
+            "notebookName": "07_MAC_+_Qwen2-7B-Instructi_Unsloth_train",
+            "widgets": {}
+        },
+        "colab": {
+            "gpuType": "T4",
+            "provenance": []
+        },
+        "kernelspec": {
+            "display_name": "Python 3",
+            "name": "python3"
+        },
+        "language_info": {
+            "codemirror_mode": {
+                "name": "ipython",
+                "version": 3
+            },
+            "file_extension": ".py",
+            "mimetype": "text/x-python",
+            "name": "python",
+            "nbconvert_exporter": "python",
+            "pygments_lexer": "ipython3",
+            "version": "3.11.9"
+        }
+    },
+    "nbformat": 4,
+    "nbformat_minor": 0
+}
diff --git a/scripts/eval-epochs.sh b/scripts/eval-epochs.sh
new file mode 100755
index 0000000000000000000000000000000000000000..74f47db1fa0b649ec66350ab0c23c69ebe033359
--- /dev/null
+++ b/scripts/eval-epochs.sh
@@ -0,0 +1,22 @@
+#!/bin/sh
+
+BASEDIR=$(dirname "$0")
+cd $BASEDIR/..
+echo Current Directory:
+pwd
+
+export LOGICAL_REASONING_DATA_PATH=datasets/mgtv
+export RESIZE_TOKEN_EMBEDDINGS=true
+export USING_LLAMA_FACTORY=true
+export USING_P1_PROMPT_TEMPLATE=false
+export LOAD_IN_4BIT=false
+
+export ORG_NAME=$1
+export MODEL=$2
+export MODEL_NAME=$ORG_NAME/$MODEL
+
+export LOGICAL_REASONING_RESULTS_PATH=data/${MODEL}_results.csv
+export ADAPTER_PATH_BASE=llama-factory/saves/$MODEL_PREFIX
+
+echo "Eval $MODEL_NAME with $ADAPTER_PATH_BASE"
+python llm_toolkit/eval_logical_reasoning_all_epochs.py
\ No newline at end of file
diff --git a/scripts/eval-mgtv-qwen2.5.sh b/scripts/eval-mgtv-qwen2.5.sh
index d9c4c5551e00910c35ee75e3ee2c3b49bbe1d022..d602490bdb4d25ca4fe11d3dc1e046c0e53b52ce 100755
--- a/scripts/eval-mgtv-qwen2.5.sh
+++ b/scripts/eval-mgtv-qwen2.5.sh
@@ -13,17 +13,12 @@ cat /etc/os-release
 lscpu
 grep MemTotal /proc/meminfo
 
-export LOGICAL_REASONING_DATA_PATH=datasets/mgtv
-export RESIZE_TOKEN_EMBEDDINGS=true
-export USING_LLAMA_FACTORY=true
-export USING_P1_PROMPT_TEMPLATE=false
-#export LOAD_IN_4BIT=true
+$BASEDIR/scripts/eval-shots.sh Qwen Qwen2.5-3B-Instruct
 
-export MODEL_PREFIX=Qwen2.5-3B-Instruct
-export MODEL_NAME=qwen/$MODEL_PREFIX
+$BASEDIR/scripts/eval-epochs.sh Qwen Qwen2.5-1.5B-Instruct
 
-export LOGICAL_REASONING_RESULTS_PATH=data/${MODEL_PREFIX}_results.csv
-export ADAPTER_PATH_BASE=llama-factory/saves/$MODEL_PREFIX
+$BASEDIR/scripts/eval-shots.sh Qwen Qwen2.5-1.5B-Instruct
 
-echo "Eval $MODEL_NAME with $ADAPTER_PATH_BASE"
-python llm_toolkit/eval_logical_reasoning_all_epochs.py
+$BASEDIR/scripts/eval-epochs.sh Qwen Qwen2.5-0.5B-Instruct
+
+$BASEDIR/scripts/eval-shots.sh Qwen Qwen2.5-0.5B-Instruct