| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: Qwen/Qwen2-1.5B |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: fine_tuned_per_domain_balanced |
| | 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_per_domain_balanced |
| |
|
| | This model is a fine-tuned version of [Qwen/Qwen2-1.5B](https://huggingface.co/Qwen/Qwen2-1.5B) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1209 |
| | - Accuracy: 0.9540 |
| |
|
| | ## 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: 32 |
| | - eval_batch_size: 32 |
| | - 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 | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 0.5664 | 0.0203 | 100 | 0.2706 | 0.8890 | |
| | | 0.2871 | 0.0406 | 200 | 0.2891 | 0.8871 | |
| | | 0.2495 | 0.0608 | 300 | 0.2310 | 0.9026 | |
| | | 0.2414 | 0.0811 | 400 | 0.1710 | 0.9290 | |
| | | 0.1983 | 0.1014 | 500 | 0.1614 | 0.9332 | |
| | | 0.198 | 0.1217 | 600 | 0.1482 | 0.9394 | |
| | | 0.2112 | 0.1419 | 700 | 0.1545 | 0.9443 | |
| | | 0.1791 | 0.1622 | 800 | 0.1303 | 0.9501 | |
| | | 0.1707 | 0.1825 | 900 | 0.1822 | 0.9340 | |
| | | 0.1663 | 0.2028 | 1000 | 0.1297 | 0.9511 | |
| | | 0.1657 | 0.2230 | 1100 | 0.1433 | 0.9492 | |
| | | 0.1467 | 0.2433 | 1200 | 0.1107 | 0.9590 | |
| | | 0.1519 | 0.2636 | 1300 | 0.1250 | 0.9548 | |
| | | 0.1474 | 0.2839 | 1400 | 0.1045 | 0.9613 | |
| | | 0.1509 | 0.3041 | 1500 | 0.1180 | 0.9593 | |
| | | 0.147 | 0.3244 | 1600 | 0.1076 | 0.9588 | |
| | | 0.1308 | 0.3447 | 1700 | 0.1209 | 0.9540 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.49.0 |
| | - Pytorch 2.6.0+cu126 |
| | - Datasets 3.3.2 |
| | - Tokenizers 0.21.0 |
| |
|
