| --- |
| library_name: transformers |
| license: other |
| base_model: Qwen/Qwen1.5-1.8B |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: fine_tuned_all_domains_1.5 |
| 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_all_domains_1.5 |
|
|
| This model is a fine-tuned version of [Qwen/Qwen1.5-1.8B](https://huggingface.co/Qwen/Qwen1.5-1.8B) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2531 |
| - Accuracy: 0.9460 |
|
|
| ## 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-06 |
| - 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: 1 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | 0.4234 | 0.0126 | 500 | 0.3614 | 0.8957 | |
| | 0.2949 | 0.0252 | 1000 | 0.2974 | 0.9101 | |
| | 0.3592 | 0.0377 | 1500 | 0.2913 | 0.9137 | |
| | 0.3101 | 0.0503 | 2000 | 0.2877 | 0.9326 | |
| | 0.2923 | 0.0629 | 2500 | 0.2246 | 0.9290 | |
| | 0.2778 | 0.0755 | 3000 | 0.2472 | 0.9397 | |
| | 0.2556 | 0.0881 | 3500 | 0.2163 | 0.9487 | |
| | 0.2986 | 0.1006 | 4000 | 0.2156 | 0.9478 | |
| | 0.272 | 0.1132 | 4500 | 0.2387 | 0.9388 | |
| | 0.2363 | 0.1258 | 5000 | 0.4263 | 0.9326 | |
| | 0.221 | 0.1384 | 5500 | 0.2054 | 0.9505 | |
| | 0.2478 | 0.1510 | 6000 | 0.2851 | 0.9451 | |
| | 0.2451 | 0.1635 | 6500 | 0.2730 | 0.9442 | |
| | 0.1915 | 0.1761 | 7000 | 0.2531 | 0.9460 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.49.0 |
| - Pytorch 2.6.0+cu126 |
| - Datasets 3.3.2 |
| - Tokenizers 0.21.0 |
|
|
