Upload folder using huggingface_hub
Browse files- README.md +9 -0
- adapter_config.json +23 -0
- adapter_model.bin +3 -0
- added_tokens.json +6 -0
- checkpoint-1062/README.md +238 -0
- checkpoint-1062/adapter_config.json +23 -0
- checkpoint-1062/adapter_model.bin +3 -0
- checkpoint-1062/added_tokens.json +6 -0
- checkpoint-1062/optimizer.pt +3 -0
- checkpoint-1062/pytorch_model.bin +3 -0
- checkpoint-1062/rng_state.pth +3 -0
- checkpoint-1062/scheduler.pt +3 -0
- checkpoint-1062/special_tokens_map.json +6 -0
- checkpoint-1062/tokenizer.json +0 -0
- checkpoint-1062/tokenizer.model +3 -0
- checkpoint-1062/tokenizer_config.json +47 -0
- checkpoint-1062/trainer_state.json +25 -0
- checkpoint-1062/training_args.bin +3 -0
- runs/Oct14_17-15-40_d0c2f0f546ac/events.out.tfevents.1697303741.d0c2f0f546ac.2369.0 +3 -0
- special_tokens_map.json +6 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +47 -0
- training_args.bin +3 -0
- training_params.json +1 -0
README.md
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---
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tags:
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- autotrain
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- text-generation
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widget:
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- text: "I love AutoTrain because "
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---
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# Model Trained Using AutoTrain
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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": "NousResearch/Llama-2-7b-chat-hf",
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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": 32,
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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": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"q_proj",
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"v_proj"
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],
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"task_type": "CAUSAL_LM"
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}
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adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:3b86419f792e1b9f4e6005278893b3c1dba28a008034bd7eb62676877cbd7c9b
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size 33600906
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added_tokens.json
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{
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"</s>": 2,
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"<pad>": 32000,
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"<s>": 1,
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"<unk>": 0
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}
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checkpoint-1062/README.md
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---
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library_name: peft
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base_model: NousResearch/Llama-2-7b-chat-hf
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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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- **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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|
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### Out-of-Scope Use
|
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|
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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 Data 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 Data 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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|
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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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|
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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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|
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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: nf4
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float16
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### Framework versions
|
217 |
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|
218 |
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- PEFT 0.6.0.dev0
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## Training procedure
|
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|
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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: nf4
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float16
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### Framework versions
|
236 |
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|
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|
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- PEFT 0.6.0.dev0
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checkpoint-1062/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": "NousResearch/Llama-2-7b-chat-hf",
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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": 32,
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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": 16,
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"rank_pattern": {},
|
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"revision": null,
|
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"target_modules": [
|
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"q_proj",
|
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"v_proj"
|
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],
|
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"task_type": "CAUSAL_LM"
|
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}
|
checkpoint-1062/adapter_model.bin
ADDED
@@ -0,0 +1,3 @@
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|
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1 |
+
version https://git-lfs.github.com/spec/v1
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2 |
+
oid sha256:3b86419f792e1b9f4e6005278893b3c1dba28a008034bd7eb62676877cbd7c9b
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size 33600906
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checkpoint-1062/added_tokens.json
ADDED
@@ -0,0 +1,6 @@
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1 |
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{
|
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"</s>": 2,
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"<pad>": 32000,
|
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"<s>": 1,
|
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"<unk>": 0
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}
|
checkpoint-1062/optimizer.pt
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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{"model": "NousResearch/Llama-2-7b-chat-hf", "data_path": "timdettmers/openassistant-guanaco", "project_name": "testLlama2", "train_split": "train", "valid_split": null, "text_column": "text", "rejected_text_column": "rejected", "lr": 0.0002, "epochs": 1, "batch_size": 1, "warmup_ratio": 0.1, "gradient_accumulation": 4, "optimizer": "adamw_torch", "scheduler": "linear", "weight_decay": 0.01, "max_grad_norm": 1.0, "seed": 42, "add_eos_token": false, "block_size": 1024, "use_peft": true, "lora_r": 16, "lora_alpha": 32, "lora_dropout": 0.05, "logging_steps": -1, "evaluation_strategy": "epoch", "save_total_limit": 1, "save_strategy": "epoch", "auto_find_batch_size": false, "fp16": true, "push_to_hub": true, "use_int8": false, "model_max_length": 1024, "repo_id": "Cesar42/TrainLlama2Dataset2", "use_int4": true, "trainer": "default", "target_modules": null, "merge_adapter": false, "username": null, "use_flash_attention_2": false, "disable_gradient_checkpointing": false}
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