<!-- 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_epo3_batchsize8
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6683
- Precision: 0.6289
- Recall: 0.6035
- F1: 0.6124
- Accuracy: 0.782
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.8489 | 1.0 | 750 | 0.5924 | 0.6066 | 0.5512 | 0.5605 | 0.782 |
| 0.5551 | 2.0 | 1500 | 0.6388 | 0.6112 | 0.5513 | 0.5698 | 0.7745 |
| 0.4379 | 3.0 | 2250 | 0.6683 | 0.6289 | 0.6035 | 0.6124 | 0.782 |
Framework versions
- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
