| --- |
| base_model: NousResearch/Llama-2-7b-hf |
| library_name: peft |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: Experiment-2 |
| 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. --> |
|
|
| # Experiment-2 |
|
|
| This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6750 |
| - Accuracy: 0.596 |
| - Precision: 0.5869 |
| - Recall: 0.6263 |
| - F1: 0.6060 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - gradient_accumulation_steps: 16 |
| - total_train_batch_size: 64 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | No log | 0.9874 | 54 | 0.6970 | 0.532 | 0.5313 | 0.4785 | 0.5035 | |
| | No log | 1.9931 | 109 | 0.6923 | 0.508 | 0.5103 | 0.1989 | 0.2863 | |
| | 0.694 | 2.9989 | 164 | 0.6888 | 0.5413 | 0.5303 | 0.6586 | 0.5875 | |
| | 0.694 | 3.9863 | 218 | 0.6926 | 0.5187 | 0.6279 | 0.0726 | 0.1301 | |
| | 0.694 | 4.992 | 273 | 0.6778 | 0.5947 | 0.6269 | 0.4516 | 0.525 | |
| | 0.6841 | 5.9977 | 328 | 0.6738 | 0.5827 | 0.5582 | 0.7608 | 0.6439 | |
| | 0.6841 | 6.9851 | 382 | 0.6701 | 0.5893 | 0.6301 | 0.4167 | 0.5016 | |
| | 0.6841 | 7.9909 | 437 | 0.6717 | 0.6013 | 0.5835 | 0.6855 | 0.6304 | |
| | 0.6699 | 8.9966 | 492 | 0.6768 | 0.5787 | 0.5553 | 0.7554 | 0.6401 | |
| | 0.6699 | 9.8743 | 540 | 0.6750 | 0.596 | 0.5869 | 0.6263 | 0.6060 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.14.0 |
| - Transformers 4.46.3 |
| - Pytorch 2.3.1.post300 |
| - Datasets 3.2.0 |
| - Tokenizers 0.20.3 |
