bert-base-uncased-finetuned-filtered-0602
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1959
- Accuracy: 0.9783
- F1: 0.9783
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 | F1 |
|---|---|---|---|---|---|
| 0.1777 | 1.0 | 3180 | 0.2118 | 0.9563 | 0.9566 |
| 0.1409 | 2.0 | 6360 | 0.1417 | 0.9736 | 0.9736 |
| 0.1035 | 3.0 | 9540 | 0.1454 | 0.9739 | 0.9739 |
| 0.0921 | 4.0 | 12720 | 0.1399 | 0.9755 | 0.9755 |
| 0.0607 | 5.0 | 15900 | 0.1150 | 0.9792 | 0.9792 |
| 0.0331 | 6.0 | 19080 | 0.1770 | 0.9758 | 0.9758 |
| 0.0289 | 7.0 | 22260 | 0.1782 | 0.9767 | 0.9767 |
| 0.0058 | 8.0 | 25440 | 0.1877 | 0.9796 | 0.9796 |
| 0.008 | 9.0 | 28620 | 0.2034 | 0.9764 | 0.9764 |
| 0.0017 | 10.0 | 31800 | 0.1959 | 0.9783 | 0.9783 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.12.1