bert-finetuned-win_file
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0149
- Precision: 0.9566
- Recall: 0.9935
- F1: 0.9747
- Accuracy: 0.9962
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1053 | 1.0 | 938 | 0.0163 | 0.9550 | 0.9931 | 0.9736 | 0.9957 |
| 0.0123 | 2.0 | 1876 | 0.0149 | 0.9566 | 0.9935 | 0.9747 | 0.9962 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3