| --- |
| library_name: peft |
| license: llama3.2 |
| base_model: meta-llama/Llama-3.2-1B |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: results |
| 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. --> |
|
|
| # results |
|
|
| This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1207 |
| - Accuracy: 0.9755 |
| - Precision: 0.7225 |
| - Recall: 0.7652 |
| - F1: 0.7432 |
|
|
| ## 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: 0.0002 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - 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: cosine |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | No log | 1.0 | 204 | 0.0963 | 0.9710 | 0.6434 | 0.6814 | 0.6619 | |
| | No log | 2.0 | 408 | 0.0877 | 0.9742 | 0.6677 | 0.7389 | 0.7015 | |
| | 0.1244 | 3.0 | 612 | 0.0957 | 0.9723 | 0.7054 | 0.6880 | 0.6966 | |
| | 0.1244 | 4.0 | 816 | 0.0903 | 0.9759 | 0.7323 | 0.7635 | 0.7476 | |
| | 0.0318 | 5.0 | 1020 | 0.1059 | 0.9732 | 0.6986 | 0.7192 | 0.7087 | |
| | 0.0318 | 6.0 | 1224 | 0.1025 | 0.9758 | 0.7179 | 0.7438 | 0.7306 | |
| | 0.0318 | 7.0 | 1428 | 0.1177 | 0.9742 | 0.7072 | 0.7455 | 0.7258 | |
| | 0.0136 | 8.0 | 1632 | 0.1172 | 0.9754 | 0.7134 | 0.7603 | 0.7361 | |
| | 0.0136 | 9.0 | 1836 | 0.1199 | 0.9755 | 0.7229 | 0.7668 | 0.7442 | |
| | 0.009 | 10.0 | 2040 | 0.1207 | 0.9755 | 0.7225 | 0.7652 | 0.7432 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.15.2 |
| - Transformers 4.52.4 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.2 |
