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  1. README.md +62 -180
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README.md CHANGED
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  ---
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- library_name: transformers
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- tags: []
 
 
 
 
 
 
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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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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- - **Developed by:** [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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- [More Information Needed]
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- ### Downstream Use [optional]
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- ## Bias, Risks, and Limitations
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- ### Recommendations
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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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- ## Training Details
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- ### Training Data
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- ### Training Procedure
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- #### Preprocessing [optional]
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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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- ## Evaluation
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- #### Factors
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- #### Metrics
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- ### Results
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- #### Summary
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- ## Model Examination [optional]
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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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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- ## Glossary [optional]
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- ## More Information [optional]
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  ---
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+ base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
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+ library_name: peft
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: shawgpt-ft
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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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+ # shawgpt-ft
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+ This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.7402
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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: 8e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 16
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 2
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+ - num_epochs: 20
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+ - mixed_precision_training: Native AMP
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+ ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-------:|:----:|:---------------:|
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+ | 4.6249 | 0.9231 | 3 | 4.1254 |
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+ | 4.3778 | 1.8462 | 6 | 3.8852 |
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+ | 4.0877 | 2.7692 | 9 | 3.6541 |
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+ | 2.8518 | 4.0 | 13 | 3.3539 |
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+ | 3.5577 | 4.9231 | 16 | 3.1426 |
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+ | 3.3003 | 5.8462 | 19 | 2.9494 |
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+ | 3.0846 | 6.7692 | 22 | 2.7761 |
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+ | 2.1597 | 8.0 | 26 | 2.5710 |
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+ | 2.6927 | 8.9231 | 29 | 2.4270 |
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+ | 2.5126 | 9.8462 | 32 | 2.3068 |
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+ | 2.3827 | 10.7692 | 35 | 2.1855 |
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+ | 1.6467 | 12.0 | 39 | 2.0325 |
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+ | 2.0858 | 12.9231 | 42 | 1.9558 |
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+ | 1.9783 | 13.8462 | 45 | 1.8930 |
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+ | 1.9199 | 14.7692 | 48 | 1.8388 |
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+ | 1.3996 | 16.0 | 52 | 1.7856 |
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+ | 1.8117 | 16.9231 | 55 | 1.7594 |
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+ | 1.7748 | 17.8462 | 58 | 1.7441 |
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+ | 1.234 | 18.4615 | 60 | 1.7402 |
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+ ### Framework versions
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+ - PEFT 0.13.2
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+ - Transformers 4.45.2
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+ - Pytorch 2.5.0+cu124
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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