Tatvajsh/AHS_OPS_and_WPCS_DPO_TEST
Browse files- README.md +56 -0
- adapter_config.json +29 -0
- adapter_model.safetensors +3 -0
- final_checkpoint/README.md +220 -0
- final_checkpoint/adapter_config.json +29 -0
- final_checkpoint/adapter_model.safetensors +3 -0
- runs/Nov17_00-34-18_72015118f6f0/events.out.tfevents.1700181261.72015118f6f0.13110.0 +3 -0
- special_tokens_map.json +24 -0
- tokenizer.model +3 -0
- tokenizer_config.json +41 -0
- training_args.bin +3 -0
README.md
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---
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license: apache-2.0
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base_model: openlm-research/open_llama_3b_v2
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tags:
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- generated_from_trainer
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model-index:
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- name: results
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# results
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This model is a fine-tuned version of [openlm-research/open_llama_3b_v2](https://huggingface.co/openlm-research/open_llama_3b_v2) on the None dataset.
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0005
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 100
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- num_epochs: 3.0
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- mixed_precision_training: Native AMP
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### Training results
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### Framework versions
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- Transformers 4.36.0.dev0
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- Pytorch 2.1.0+cu118
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "openlm-research/open_llama_3b_v2",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layers_pattern": null,
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"layers_to_transform": null,
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"lora_alpha": 16,
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"lora_dropout": 0.05,
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 8,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"k_proj",
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"up_proj",
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"gate_proj",
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"v_proj",
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"base_layer",
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"q_proj",
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"down_proj",
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"o_proj"
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],
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"task_type": "CAUSAL_LM"
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:55bd7e08330b513c44514e16e8a1338069bc93c308a9e1a29b5044b98b7e2287
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size 50899792
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final_checkpoint/README.md
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---
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library_name: peft
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base_model: openlm-research/open_llama_3b_v2
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- 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. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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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).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- 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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[More Information Needed]
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**APA:**
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[More Information Needed]
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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 Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: bitsandbytes
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- load_in_8bit: False
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- load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: fp4
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float32
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### Framework versions
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- PEFT 0.6.3.dev0
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final_checkpoint/adapter_config.json
ADDED
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "openlm-research/open_llama_3b_v2",
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"bias": "none",
|
6 |
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layers_pattern": null,
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"layers_to_transform": null,
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"lora_alpha": 16,
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"lora_dropout": 0.05,
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 8,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"k_proj",
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"up_proj",
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"gate_proj",
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"v_proj",
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23 |
+
"base_layer",
|
24 |
+
"q_proj",
|
25 |
+
"down_proj",
|
26 |
+
"o_proj"
|
27 |
+
],
|
28 |
+
"task_type": "CAUSAL_LM"
|
29 |
+
}
|
final_checkpoint/adapter_model.safetensors
ADDED
@@ -0,0 +1,3 @@
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1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:55bd7e08330b513c44514e16e8a1338069bc93c308a9e1a29b5044b98b7e2287
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size 50899792
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runs/Nov17_00-34-18_72015118f6f0/events.out.tfevents.1700181261.72015118f6f0.13110.0
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:05ce77a89f846e4f3ed340429a4fa5284a78e4ca10da0c77e266c7d7c6131b88
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size 5076
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special_tokens_map.json
ADDED
@@ -0,0 +1,24 @@
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|
1 |
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{
|
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|
3 |
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"content": "<s>",
|
4 |
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"lstrip": false,
|
5 |
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"normalized": true,
|
6 |
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"rstrip": false,
|
7 |
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"single_word": false
|
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},
|
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"eos_token": {
|
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"content": "</s>",
|
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|
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|
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"rstrip": false,
|
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|
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},
|
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"pad_token": "<p>",
|
17 |
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"unk_token": {
|
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"content": "<unk>",
|
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|
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"normalized": true,
|
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"rstrip": false,
|
22 |
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"single_word": false
|
23 |
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}
|
24 |
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}
|
tokenizer.model
ADDED
@@ -0,0 +1,3 @@
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1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:91b289e85fa20fd375d8b33dc12f77616f18abc6359804471d1fafcb425fecb8
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size 511574
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tokenizer_config.json
ADDED
@@ -0,0 +1,41 @@
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|
1 |
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{
|
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"add_bos_token": true,
|
3 |
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"add_eos_token": false,
|
4 |
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"added_tokens_decoder": {
|
5 |
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"0": {
|
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|
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|
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|
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|
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"single_word": false,
|
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"special": true
|
12 |
+
},
|
13 |
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"1": {
|
14 |
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"content": "<s>",
|
15 |
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|
16 |
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"normalized": true,
|
17 |
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"rstrip": false,
|
18 |
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"single_word": false,
|
19 |
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"special": true
|
20 |
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},
|
21 |
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"2": {
|
22 |
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"content": "</s>",
|
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|
24 |
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|
25 |
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|
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"single_word": false,
|
27 |
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"special": true
|
28 |
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}
|
29 |
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},
|
30 |
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"bos_token": "<s>",
|
31 |
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"clean_up_tokenization_spaces": false,
|
32 |
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"eos_token": "</s>",
|
33 |
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"legacy": true,
|
34 |
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"model_max_length": 2048,
|
35 |
+
"pad_token": "<p>",
|
36 |
+
"sp_model_kwargs": {},
|
37 |
+
"spaces_between_special_tokens": false,
|
38 |
+
"tokenizer_class": "LlamaTokenizer",
|
39 |
+
"unk_token": "<unk>",
|
40 |
+
"use_default_system_prompt": false
|
41 |
+
}
|
training_args.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:8c9fa84eb2fcacd951f172ac55836679ab6eea4078fe85a94ba2ecea341af6d1
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size 4664
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