bert-base-cased-news-16batch_5epoch_2e5lr_1wd
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: 0.3683
- F1: 0.9276
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: 47
- 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 | F1 |
|---|---|---|---|---|
| 0.0615 | 1.0 | 3124 | 0.1887 | 0.9221 |
| 0.0382 | 2.0 | 6248 | 0.2401 | 0.9240 |
| 0.0208 | 3.0 | 9372 | 0.2618 | 0.9265 |
| 0.0026 | 4.0 | 12496 | 0.3209 | 0.9230 |
| 0.0029 | 5.0 | 15620 | 0.3683 | 0.9276 |
Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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