| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: FacebookAI/roberta-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - accuracy |
| | model-index: |
| | - name: roberta-base-pr_tqacd |
| | 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. --> |
| |
|
| | # roberta-base-pr_tqacd |
| | |
| | This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.6056 |
| | - F1 Macro: 0.5289 |
| | - Precision: 0.5397 |
| | - Recall: 0.5373 |
| | - Accuracy: 0.7180 |
| | |
| | ## 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: 16 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 20 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | F1 Macro | Precision | Recall | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:| |
| | | No log | 1.0 | 354 | 1.8365 | 0.3820 | 0.4312 | 0.4000 | 0.6106 | |
| | | 2.2658 | 2.0 | 708 | 1.3285 | 0.5013 | 0.5037 | 0.5722 | 0.6554 | |
| | | 1.5226 | 3.0 | 1062 | 1.2491 | 0.5450 | 0.5421 | 0.6006 | 0.7090 | |
| | | 1.5226 | 4.0 | 1416 | 1.3314 | 0.5476 | 0.5555 | 0.5767 | 0.7180 | |
| | | 1.1009 | 5.0 | 1770 | 1.4114 | 0.5468 | 0.5457 | 0.5754 | 0.7203 | |
| | | 0.7195 | 6.0 | 2124 | 1.6056 | 0.5289 | 0.5397 | 0.5373 | 0.7180 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.57.1 |
| | - Pytorch 2.8.0+cu128 |
| | - Datasets 4.4.1 |
| | - Tokenizers 0.22.1 |
| | |
