roberta-base-finetuned-filtered-0609
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1343
- Accuracy: 0.9824
- Precision: 0.9824
- Recall: 0.9824
- F1: 0.9824
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.1817 | 1.0 | 3180 | 0.1883 | 0.9651 | 0.9654 | 0.9651 | 0.9651 |
| 0.1647 | 2.0 | 6360 | 0.1264 | 0.9777 | 0.9778 | 0.9777 | 0.9777 |
| 0.1295 | 3.0 | 9540 | 0.1514 | 0.9723 | 0.9724 | 0.9723 | 0.9723 |
| 0.0991 | 4.0 | 12720 | 0.1487 | 0.9761 | 0.9763 | 0.9761 | 0.9761 |
| 0.0749 | 5.0 | 15900 | 0.1119 | 0.9802 | 0.9802 | 0.9802 | 0.9802 |
| 0.0532 | 6.0 | 19080 | 0.1357 | 0.9789 | 0.9790 | 0.9789 | 0.9789 |
| 0.0471 | 7.0 | 22260 | 0.1397 | 0.9780 | 0.9782 | 0.9780 | 0.9780 |
| 0.0153 | 8.0 | 25440 | 0.1568 | 0.9777 | 0.9778 | 0.9777 | 0.9777 |
| 0.0147 | 9.0 | 28620 | 0.1274 | 0.9824 | 0.9824 | 0.9824 | 0.9824 |
| 0.0135 | 10.0 | 31800 | 0.1343 | 0.9824 | 0.9824 | 0.9824 | 0.9824 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.9.1+cu111
- Datasets 1.16.1
- Tokenizers 0.12.1