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final_model_category
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0769
- F1: 0.9648
- Roc Auc: 0.9727
- Accuracy: 0.9129
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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.1418 | 1.0 | 3445 | 0.1373 | 0.9339 | 0.9495 | 0.8409 |
| 0.124 | 2.0 | 6890 | 0.1221 | 0.9411 | 0.9534 | 0.8571 |
| 0.1201 | 3.0 | 10335 | 0.1123 | 0.9466 | 0.9592 | 0.8705 |
| 0.0918 | 4.0 | 13780 | 0.0933 | 0.9547 | 0.9640 | 0.8891 |
| 0.0779 | 5.0 | 17225 | 0.0804 | 0.9635 | 0.9712 | 0.9129 |
| 0.0694 | 6.0 | 20670 | 0.0769 | 0.9648 | 0.9727 | 0.9129 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
