| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: Qwen/Qwen2-1.5B |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: fine_tuned_hswag_callback10 |
| 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. --> |
|
|
| # fine_tuned_hswag_callback10 |
| |
| This model is a fine-tuned version of [Qwen/Qwen2-1.5B](https://huggingface.co/Qwen/Qwen2-1.5B) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1861 |
| - Accuracy: 0.9602 |
| |
| ## 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: 2e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - 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: linear |
| - num_epochs: 3 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | 0.7551 | 0.0322 | 100 | 0.4489 | 0.9012 | |
| | 0.3977 | 0.0644 | 200 | 0.5959 | 0.8943 | |
| | 0.3608 | 0.0966 | 300 | 0.2267 | 0.9258 | |
| | 0.3092 | 0.1287 | 400 | 0.1801 | 0.9374 | |
| | 0.1932 | 0.1609 | 500 | 0.1921 | 0.9562 | |
| | 0.1405 | 0.1931 | 600 | 0.2487 | 0.9573 | |
| | 0.3093 | 0.2253 | 700 | 0.1245 | 0.9573 | |
| | 0.1804 | 0.2575 | 800 | 0.1496 | 0.9602 | |
| | 0.1717 | 0.2897 | 900 | 0.1923 | 0.9573 | |
| | 0.1986 | 0.3219 | 1000 | 0.4235 | 0.9167 | |
| | 0.1786 | 0.3540 | 1100 | 0.1436 | 0.9591 | |
| | 0.1563 | 0.3862 | 1200 | 0.2635 | 0.9468 | |
| | 0.188 | 0.4184 | 1300 | 0.1891 | 0.9540 | |
| | 0.137 | 0.4506 | 1400 | 0.2017 | 0.9348 | |
| | 0.1438 | 0.4828 | 1500 | 0.1510 | 0.9660 | |
| | 0.1241 | 0.5150 | 1600 | 0.2152 | 0.9551 | |
| | 0.1793 | 0.5472 | 1700 | 0.1861 | 0.9602 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.49.0 |
| - Pytorch 2.6.0+cu126 |
| - Datasets 3.3.2 |
| - Tokenizers 0.21.0 |
| |
