| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: FacebookAI/roberta-large |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - accuracy |
| | model-index: |
| | - name: roberta-large-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-large-tqacd |
| |
|
| | This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 3.8956 |
| | - F1 Macro: 0.2608 |
| | - Precision: 0.3007 |
| | - Recall: 0.2456 |
| | - Accuracy: 0.4158 |
| |
|
| | ## 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 | 114 | 2.4069 | 0.0094 | 0.0050 | 0.0909 | 0.0545 | |
| | | No log | 2.0 | 228 | 2.3298 | 0.1595 | 0.2519 | 0.1597 | 0.3366 | |
| | | No log | 3.0 | 342 | 2.2454 | 0.1746 | 0.2033 | 0.2052 | 0.2475 | |
| | | No log | 4.0 | 456 | 2.1684 | 0.2588 | 0.2830 | 0.2813 | 0.3614 | |
| | | 2.2272 | 5.0 | 570 | 2.3380 | 0.2425 | 0.2709 | 0.2786 | 0.3515 | |
| | | 2.2272 | 6.0 | 684 | 2.4213 | 0.3017 | 0.3142 | 0.3231 | 0.3713 | |
| | | 2.2272 | 7.0 | 798 | 2.7961 | 0.3100 | 0.3442 | 0.3141 | 0.3911 | |
| | | 2.2272 | 8.0 | 912 | 3.0757 | 0.2478 | 0.2576 | 0.2722 | 0.3614 | |
| | | 0.6491 | 9.0 | 1026 | 3.8956 | 0.2608 | 0.3007 | 0.2456 | 0.4158 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.57.1 |
| | - Pytorch 2.8.0+cu128 |
| | - Datasets 4.4.1 |
| | - Tokenizers 0.22.1 |
| |
|
