distilbert-base-uncased-finetuned
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1137
- Accuracy: 0.9733
- F1: 0.9743
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.0868 | 1.0 | 1370 | 0.1098 | 0.9729 | 0.9738 |
| 0.0598 | 2.0 | 2740 | 0.1137 | 0.9733 | 0.9743 |
| 0.0383 | 3.0 | 4110 | 0.1604 | 0.9721 | 0.9731 |
| 0.0257 | 4.0 | 5480 | 0.1671 | 0.9717 | 0.9729 |
| 0.016 | 5.0 | 6850 | 0.1904 | 0.9709 | 0.9720 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.9.0
- Datasets 2.5.1
- Tokenizers 0.10.3