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https:/huggingface.co/zjc664656505/test_repo/README.md

@@ -1,214 +0,0 @@
----
-library_name: peft
-tags:
-- generated_from_trainer
-base_model: /GenAI4HW/llama2_13b
-metrics:
-- accuracy
-model-index:
-- name: outputs/llama2-13B-lora-QuArch_0_1_1_alpaca_filtered-answer-context-test-new
-  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. -->
-
-[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
-<details><summary>See axolotl config</summary>
-
-axolotl version: `0.4.0`
-```yaml
-## General
-# base_model: meta-llama/Meta-Llama-3-8B-Instruct
-base_model: /GenAI4HW/llama2_13b
-# base_model: meta-llama/Llama-2-13b
-model_type: LlamaForCausalLM
-tokenizer_type: AutoTokenizer
-# tokenizer_type: LlamaTokenizer
-output_dir: ./outputs/llama2-13B-lora-QuArch_0_1_1_alpaca_filtered-answer-context-test-new
-seed: 42
-
-## Data Configuration
-datasets:
-  # - path: ./data/QuArch_v0_1_0_alpaca_w_context.json             # With abstract
-  # - path: ./data/QuArch_v0_1_1_alpaca_format.json                # With justification
-  # - path: ./data/QuArch_v0_1_0_alpaca_mmlu.json                  # Without justification
-  - path: ./data/QuArch_v0_1_1_alpaca_filtered_context/ 
-    type: alpaca
-    data_file: train
-    
-dataset_prepared_path:
-
-test_datasets:
-  - path: ./data/QuArch_v0_1_1_alpaca_filtered_context/
-    type: alpaca
-    split: test
-    data_file: 
-        - test  
-  
-  # - path: ./data/QuArch_v0_1_1_alpaca_filtered_context/
-  #   type: alpaca
-  #   split: val
-  #   data_file: 
-  #       - val
-
-## Model Configuration
-load_in_8bit: false
-load_in_4bit: false
-strict: false
-bf16: auto
-fp16:
-tf32: false
-device_map: 'auto'  
-
-## LoRA Configuration
-adapter: lora
-lora_r: 32
-lora_alpha: 16
-lora_dropout: 0.05
-lora_target_linear: true
-lora_model_dir:
-lora_fan_in_fan_out:
-
-## Logging Configuration
-logging_dir: ./logs
-logging_steps: 10
-wandb_project: 
-wandb_entity: 
-wandb_watch: 
-wandb_name: 
-wandb_log_model: 
-
-do_eval: true
-## Training Configuration
-sequence_len: 1024
-sample_packing: true
-pad_to_sequence_len: true
-train_on_inputs: false
-group_by_length: false
-micro_batch_size: 1
-gradient_accumulation_steps: 16
-num_epochs: 30
-warmup_steps: 10 
-weight_decay: 0.01
-optimizer: adamw_torch
-lr_scheduler: linear
-learning_rate: 2e-5
-gradient_checkpointing: false
-saves_per_epoch: 1
-# save_steps: 0
-# save_strategy: steps
-save_total_limit: 30
-load_best_model_at_end: true
-greater_is_better: true
-early_stopping_patience:
-resume_from_checkpoint:
-remove_unused_columns: true
-
-## Evaluation Configuration
-eval_sample_packing: False
-eval_batch_size: 1
-evals_per_epoch: 1
-# evaluation_strategy: epoch
-eval_max_new_tokens: 32
-eval_table_size:
-# max_new_token: 32
-# eval_causal_lm_metrics: sacrebleu
-
-# Others
-local_rank: 
-xformers_attention:
-flash_attention: true
-s2_attention:
-debug:
-deepspeed:
-fsdp:
-fsdp_config:
-special_tokens:
-    # pad_token: <|end_of_text|>
-```
-
-</details><br>
-
-# outputs/llama2-13B-lora-QuArch_0_1_1_alpaca_filtered-answer-context-test-new
-
-This model was trained from scratch on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.0432
-- Accuracy: 0.9808
-
-## 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: 2e-05
-- train_batch_size: 1
-- eval_batch_size: 1
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 2
-- gradient_accumulation_steps: 16
-- total_train_batch_size: 32
-- total_eval_batch_size: 2
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 10
-- num_epochs: 30
-
-### Training results
-
-| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
-|:-------------:|:-------:|:----:|:---------------:|:--------:|
-| No log        | 0.2105  | 1    | 5.1322          | 0.6154   |
-| No log        | 0.8421  | 4    | 5.1271          | 0.6346   |
-| No log        | 1.6842  | 8    | 5.0601          | 0.6538   |
-| 5.1323        | 2.5263  | 12   | 4.7743          | 0.7885   |
-| 5.1323        | 3.3684  | 16   | 4.0491          | 0.9231   |
-| 4.2735        | 4.2105  | 20   | 2.6444          | 0.8846   |
-| 4.2735        | 5.0526  | 24   | 1.0551          | 0.9615   |
-| 4.2735        | 5.8947  | 28   | 0.4698          | 0.6923   |
-| 1.2232        | 6.7368  | 32   | 0.3224          | 0.6731   |
-| 1.2232        | 7.5789  | 36   | 0.2527          | 1.0      |
-| 0.3083        | 8.4211  | 40   | 0.1972          | 1.0      |
-| 0.3083        | 9.2632  | 44   | 0.1372          | 0.9615   |
-| 0.3083        | 10.1053 | 48   | 0.0803          | 1.0      |
-| 0.1761        | 10.9474 | 52   | 0.0575          | 0.9808   |
-| 0.1761        | 11.7895 | 56   | 0.0475          | 0.9808   |
-| 0.116         | 12.6316 | 60   | 0.0444          | 0.9808   |
-| 0.116         | 13.4737 | 64   | 0.0463          | 0.9808   |
-| 0.116         | 14.3158 | 68   | 0.0489          | 0.9808   |
-| 0.0814        | 15.1579 | 72   | 0.0495          | 0.9808   |
-| 0.0814        | 16.0    | 76   | 0.0481          | 0.9808   |
-| 0.0709        | 16.8421 | 80   | 0.0469          | 0.9808   |
-| 0.0709        | 17.6842 | 84   | 0.0457          | 0.9808   |
-| 0.0709        | 18.5263 | 88   | 0.0455          | 0.9808   |
-| 0.0632        | 19.3684 | 92   | 0.0454          | 0.9808   |
-| 0.0632        | 20.2105 | 96   | 0.0459          | 0.9808   |
-| 0.0569        | 21.0526 | 100  | 0.0458          | 0.9808   |
-| 0.0569        | 21.8947 | 104  | 0.0446          | 0.9808   |
-| 0.0569        | 22.7368 | 108  | 0.0451          | 0.9808   |
-| 0.055         | 23.5789 | 112  | 0.0446          | 0.9808   |
-| 0.055         | 24.4211 | 116  | 0.0452          | 0.9808   |
-| 0.0581        | 25.2632 | 120  | 0.0432          | 0.9808   |
-
-
-### Framework versions
-
-- PEFT 0.10.0
-- Transformers 4.41.2
-- Pytorch 2.1.2+cu121
-- Datasets 2.19.1
-- Tokenizers 0.19.1

https:/huggingface.co/zjc664656505/test_repo/adapter_config.json

@@ -1,34 +0,0 @@
-{
-  "alpha_pattern": {},
-  "auto_mapping": null,
-  "base_model_name_or_path": "/GenAI4HW/llama2_13b",
-  "bias": "none",
-  "fan_in_fan_out": null,
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-  "init_lora_weights": true,
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-  "loftq_config": {},
-  "lora_alpha": 16,
-  "lora_dropout": 0.05,
-  "megatron_config": null,
-  "megatron_core": "megatron.core",
-  "modules_to_save": null,
-  "peft_type": "LORA",
-  "r": 32,
-  "rank_pattern": {},
-  "revision": null,
-  "target_modules": [
-    "k_proj",
-    "o_proj",
-    "v_proj",
-    "q_proj",
-    "down_proj",
-    "up_proj",
-    "gate_proj"
-  ],
-  "task_type": "CAUSAL_LM",
-  "use_dora": false,
-  "use_rslora": false
-}

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https:/huggingface.co/zjc664656505/test_repo/checkpoint-36/README.md

@@ -1,202 +0,0 @@
----
-library_name: peft
-base_model: /GenAI4HW/llama2_13b
----
-
-# 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 0.10.0

https:/huggingface.co/zjc664656505/test_repo/checkpoint-36/adapter_config.json

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-{
-  "alpha_pattern": {},
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-    "o_proj",
-    "v_proj",
-    "q_proj",
-    "down_proj",
-    "up_proj",
-    "gate_proj"
-  ],
-  "task_type": "CAUSAL_LM",
-  "use_dora": false,
-  "use_rslora": false
-}

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-{
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-{
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-  "tokenizer_class": "LlamaTokenizer",
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-  "use_default_system_prompt": false
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https:/huggingface.co/zjc664656505/test_repo/checkpoint-36/trainer_state.json

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-{
-  "best_metric": 5.127074241638184,
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----
-library_name: peft
-base_model: /GenAI4HW/llama2_13b
----
-
-# 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. -->
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-**BibTeX:**
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-## Glossary [optional]
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-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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-## More Information [optional]
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-[More Information Needed]
-
-## Model Card Authors [optional]
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-
-## Model Card Contact
-
-[More Information Needed]
-### Framework versions
-
-- PEFT 0.10.0

https:/huggingface.co/zjc664656505/test_repo/checkpoint-40/adapter_config.json

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----
-library_name: peft
-base_model: /GenAI4HW/llama2_13b
----
-
-# 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 0.10.0

https:/huggingface.co/zjc664656505/test_repo/checkpoint-48/adapter_config.json

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https:/huggingface.co/zjc664656505/test_repo/checkpoint-48/tokenizer.model

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https:/huggingface.co/zjc664656505/test_repo/checkpoint-48/trainer_state.json

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https:/huggingface.co/zjc664656505/test_repo/checkpoint-48/training_args.bin

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https:/huggingface.co/zjc664656505/test_repo/config.json

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-{
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https:/huggingface.co/zjc664656505/test_repo/special_tokens_map.json

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-{
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https:/huggingface.co/zjc664656505/test_repo/tokenizer.model

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https:/huggingface.co/zjc664656505/test_repo/tokenizer_config.json

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-{
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https:/huggingface.co/zjc664656505/test_repo/tree/main/README.md

@@ -1,214 +0,0 @@
----
-library_name: peft
-tags:
-- generated_from_trainer
-base_model: /GenAI4HW/llama2_13b
-metrics:
-- accuracy
-model-index:
-- name: outputs/llama2-13B-lora-QuArch_0_1_1_alpaca_filtered-answer-context-test-new
-  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. -->
-
-[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
-<details><summary>See axolotl config</summary>
-
-axolotl version: `0.4.0`
-```yaml
-## General
-# base_model: meta-llama/Meta-Llama-3-8B-Instruct
-base_model: /GenAI4HW/llama2_13b
-# base_model: meta-llama/Llama-2-13b
-model_type: LlamaForCausalLM
-tokenizer_type: AutoTokenizer
-# tokenizer_type: LlamaTokenizer
-output_dir: ./outputs/llama2-13B-lora-QuArch_0_1_1_alpaca_filtered-answer-context-test-new
-seed: 42
-
-## Data Configuration
-datasets:
-  # - path: ./data/QuArch_v0_1_0_alpaca_w_context.json             # With abstract
-  # - path: ./data/QuArch_v0_1_1_alpaca_format.json                # With justification
-  # - path: ./data/QuArch_v0_1_0_alpaca_mmlu.json                  # Without justification
-  - path: ./data/QuArch_v0_1_1_alpaca_filtered_context/ 
-    type: alpaca
-    data_file: train
-    
-dataset_prepared_path:
-
-test_datasets:
-  - path: ./data/QuArch_v0_1_1_alpaca_filtered_context/
-    type: alpaca
-    split: test
-    data_file: 
-        - test  
-  
-  # - path: ./data/QuArch_v0_1_1_alpaca_filtered_context/
-  #   type: alpaca
-  #   split: val
-  #   data_file: 
-  #       - val
-
-## Model Configuration
-load_in_8bit: false
-load_in_4bit: false
-strict: false
-bf16: auto
-fp16:
-tf32: false
-device_map: 'auto'  
-
-## LoRA Configuration
-adapter: lora
-lora_r: 32
-lora_alpha: 16
-lora_dropout: 0.05
-lora_target_linear: true
-lora_model_dir:
-lora_fan_in_fan_out:
-
-## Logging Configuration
-logging_dir: ./logs
-logging_steps: 10
-wandb_project: 
-wandb_entity: 
-wandb_watch: 
-wandb_name: 
-wandb_log_model: 
-
-do_eval: true
-## Training Configuration
-sequence_len: 1024
-sample_packing: true
-pad_to_sequence_len: true
-train_on_inputs: false
-group_by_length: false
-micro_batch_size: 1
-gradient_accumulation_steps: 16
-num_epochs: 30
-warmup_steps: 10 
-weight_decay: 0.01
-optimizer: adamw_torch
-lr_scheduler: linear
-learning_rate: 2e-5
-gradient_checkpointing: false
-saves_per_epoch: 1
-# save_steps: 0
-# save_strategy: steps
-save_total_limit: 30
-load_best_model_at_end: true
-greater_is_better: true
-early_stopping_patience:
-resume_from_checkpoint:
-remove_unused_columns: true
-
-## Evaluation Configuration
-eval_sample_packing: False
-eval_batch_size: 1
-evals_per_epoch: 1
-# evaluation_strategy: epoch
-eval_max_new_tokens: 32
-eval_table_size:
-# max_new_token: 32
-# eval_causal_lm_metrics: sacrebleu
-
-# Others
-local_rank: 
-xformers_attention:
-flash_attention: true
-s2_attention:
-debug:
-deepspeed:
-fsdp:
-fsdp_config:
-special_tokens:
-    # pad_token: <|end_of_text|>
-```
-
-</details><br>
-
-# outputs/llama2-13B-lora-QuArch_0_1_1_alpaca_filtered-answer-context-test-new
-
-This model was trained from scratch on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.0432
-- Accuracy: 0.9808
-
-## 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: 2e-05
-- train_batch_size: 1
-- eval_batch_size: 1
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 2
-- gradient_accumulation_steps: 16
-- total_train_batch_size: 32
-- total_eval_batch_size: 2
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 10
-- num_epochs: 30
-
-### Training results
-
-| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
-|:-------------:|:-------:|:----:|:---------------:|:--------:|
-| No log        | 0.2105  | 1    | 5.1322          | 0.6154   |
-| No log        | 0.8421  | 4    | 5.1271          | 0.6346   |
-| No log        | 1.6842  | 8    | 5.0601          | 0.6538   |
-| 5.1323        | 2.5263  | 12   | 4.7743          | 0.7885   |
-| 5.1323        | 3.3684  | 16   | 4.0491          | 0.9231   |
-| 4.2735        | 4.2105  | 20   | 2.6444          | 0.8846   |
-| 4.2735        | 5.0526  | 24   | 1.0551          | 0.9615   |
-| 4.2735        | 5.8947  | 28   | 0.4698          | 0.6923   |
-| 1.2232        | 6.7368  | 32   | 0.3224          | 0.6731   |
-| 1.2232        | 7.5789  | 36   | 0.2527          | 1.0      |
-| 0.3083        | 8.4211  | 40   | 0.1972          | 1.0      |
-| 0.3083        | 9.2632  | 44   | 0.1372          | 0.9615   |
-| 0.3083        | 10.1053 | 48   | 0.0803          | 1.0      |
-| 0.1761        | 10.9474 | 52   | 0.0575          | 0.9808   |
-| 0.1761        | 11.7895 | 56   | 0.0475          | 0.9808   |
-| 0.116         | 12.6316 | 60   | 0.0444          | 0.9808   |
-| 0.116         | 13.4737 | 64   | 0.0463          | 0.9808   |
-| 0.116         | 14.3158 | 68   | 0.0489          | 0.9808   |
-| 0.0814        | 15.1579 | 72   | 0.0495          | 0.9808   |
-| 0.0814        | 16.0    | 76   | 0.0481          | 0.9808   |
-| 0.0709        | 16.8421 | 80   | 0.0469          | 0.9808   |
-| 0.0709        | 17.6842 | 84   | 0.0457          | 0.9808   |
-| 0.0709        | 18.5263 | 88   | 0.0455          | 0.9808   |
-| 0.0632        | 19.3684 | 92   | 0.0454          | 0.9808   |
-| 0.0632        | 20.2105 | 96   | 0.0459          | 0.9808   |
-| 0.0569        | 21.0526 | 100  | 0.0458          | 0.9808   |
-| 0.0569        | 21.8947 | 104  | 0.0446          | 0.9808   |
-| 0.0569        | 22.7368 | 108  | 0.0451          | 0.9808   |
-| 0.055         | 23.5789 | 112  | 0.0446          | 0.9808   |
-| 0.055         | 24.4211 | 116  | 0.0452          | 0.9808   |
-| 0.0581        | 25.2632 | 120  | 0.0432          | 0.9808   |
-
-
-### Framework versions
-
-- PEFT 0.10.0
-- Transformers 4.41.2
-- Pytorch 2.1.2+cu121
-- Datasets 2.19.1
-- Tokenizers 0.19.1

https:/huggingface.co/zjc664656505/test_repo/tree/main/adapter_config.json

@@ -1,34 +0,0 @@
-{
-  "alpha_pattern": {},
-  "auto_mapping": null,
-  "base_model_name_or_path": "/GenAI4HW/llama2_13b",
-  "bias": "none",
-  "fan_in_fan_out": null,
-  "inference_mode": true,
-  "init_lora_weights": true,
-  "layer_replication": null,
-  "layers_pattern": null,
-  "layers_to_transform": null,
-  "loftq_config": {},
-  "lora_alpha": 16,
-  "lora_dropout": 0.05,
-  "megatron_config": null,
-  "megatron_core": "megatron.core",
-  "modules_to_save": null,
-  "peft_type": "LORA",
-  "r": 32,
-  "rank_pattern": {},
-  "revision": null,
-  "target_modules": [
-    "k_proj",
-    "o_proj",
-    "v_proj",
-    "q_proj",
-    "down_proj",
-    "up_proj",
-    "gate_proj"
-  ],
-  "task_type": "CAUSAL_LM",
-  "use_dora": false,
-  "use_rslora": false
-}

https:/huggingface.co/zjc664656505/test_repo/tree/main/adapter_model.bin

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:a485ccd9a97977dda43fef1b6f4ff1e9fe34488e04fb00f292e0630f23f6abda
-size 250550026