bert-base-uncased-finetuned-filtered-0601
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: 0.1152
- Accuracy: 0.9814
- F1: 0.9815
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 3180 | 0.1346 | 0.9664 | 0.9665 |
| No log | 2.0 | 6360 | 0.1352 | 0.9748 | 0.9749 |
| No log | 3.0 | 9540 | 0.1038 | 0.9808 | 0.9808 |
| No log | 4.0 | 12720 | 0.1152 | 0.9814 | 0.9815 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.12.1