| --- |
| library_name: peft |
| base_model: NousResearch/Llama-2-7b-hf |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: evaluation_model |
| 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. --> |
|
|
| # evaluation_model |
| |
| 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: 0.7124 |
| - Accuracy: 0.4667 |
| - Precision: 0.4577 |
| - Recall: 0.9559 |
| - F1: 0.6190 |
| |
| ## 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: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 16 |
| - optimizer: Use 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: 5 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | No log | 0.9829 | 43 | 0.9195 | 0.5467 | 0.0 | 0.0 | 0.0 | |
| | No log | 1.9943 | 87 | 0.6833 | 0.5667 | 0.5172 | 0.6618 | 0.5806 | |
| | No log | 2.9829 | 130 | 0.6898 | 0.5267 | 0.4884 | 0.9265 | 0.6396 | |
| | 0.8708 | 3.9943 | 174 | 0.6775 | 0.5667 | 0.5149 | 0.7647 | 0.6154 | |
| | 0.8708 | 4.9371 | 215 | 0.7124 | 0.4667 | 0.4577 | 0.9559 | 0.6190 | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.13.2 |
| - Transformers 4.46.2 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
