| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: Qwen/Qwen2-1.5B |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: fine_tuned_new_mage_cmv |
| | 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_new_mage_cmv |
| |
|
| | 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: 0.2763 |
| | - 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: 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 | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 1.2255 | 0.0361 | 100 | 0.2722 | 0.8960 | |
| | | 0.32 | 0.0722 | 200 | 0.3347 | 0.9326 | |
| | | 0.2638 | 0.1083 | 300 | 0.1909 | 0.9606 | |
| | | 0.4198 | 0.1445 | 400 | 0.2482 | 0.9216 | |
| | | 0.2123 | 0.1806 | 500 | 0.5727 | 0.9123 | |
| | | 0.1887 | 0.2167 | 600 | 0.2763 | 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 |
| |
|
