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BERT_PKDD-Anomaly
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0926
- Accuracy: 0.9662
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2174 | 1.0 | 1094 | 0.0992 | 0.9656 |
| 0.1167 | 2.0 | 2188 | 0.1319 | 0.957 |
| 0.1048 | 3.0 | 3282 | 0.0891 | 0.9688 |
| 0.0953 | 4.0 | 4376 | 0.0905 | 0.9702 |
| 0.0889 | 5.0 | 5470 | 0.0895 | 0.9704 |
| 0.0801 | 6.0 | 6564 | 0.0762 | 0.9724 |
| 0.0698 | 7.0 | 7658 | 0.0808 | 0.9756 |
| 0.0579 | 8.0 | 8752 | 0.0878 | 0.9774 |
| 0.0444 | 9.0 | 9846 | 0.0839 | 0.9796 |
| 0.0353 | 10.0 | 10940 | 0.0929 | 0.9798 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
