| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: Qwen/Qwen2-1.5B |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: fine_tuned_xsum |
| 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_xsum |
|
|
| 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: 0.1573 |
| - Accuracy: 0.9597 |
|
|
| ## 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 | |
| |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | 0.7991 | 0.0289 | 100 | 0.3764 | 0.8394 | |
| | 0.6153 | 0.0578 | 200 | 0.3492 | 0.8602 | |
| | 0.3929 | 0.0867 | 300 | 0.5004 | 0.8501 | |
| | 0.7981 | 0.1156 | 400 | 0.3459 | 0.8677 | |
| | 0.5853 | 0.1445 | 500 | 0.3124 | 0.8787 | |
| | 0.3284 | 0.1734 | 600 | 0.2438 | 0.9308 | |
| | 0.3591 | 0.2023 | 700 | 0.2842 | 0.9041 | |
| | 0.332 | 0.2311 | 800 | 0.3904 | 0.9038 | |
| | 0.3424 | 0.2600 | 900 | 0.2234 | 0.9402 | |
| | 0.2609 | 0.2889 | 1000 | 0.2586 | 0.9249 | |
| | 0.3036 | 0.3178 | 1100 | 0.2775 | 0.9204 | |
| | 0.2429 | 0.3467 | 1200 | 0.1521 | 0.9441 | |
| | 0.2495 | 0.3756 | 1300 | 0.2326 | 0.9512 | |
| | 0.2486 | 0.4045 | 1400 | 0.2712 | 0.9467 | |
| | 0.1711 | 0.4334 | 1500 | 0.1573 | 0.9597 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.49.0 |
| - Pytorch 2.6.0+cu126 |
| - Datasets 3.3.2 |
| - Tokenizers 0.21.0 |
|
|
