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DistilRoBERTa_PKDD-Anomaly
This model is a fine-tuned version of distilroberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0555
- Accuracy: 0.9914
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 |
---|---|---|---|---|
0.1359 | 1.0 | 1094 | 0.0651 | 0.9742 |
0.0775 | 2.0 | 2188 | 0.0659 | 0.9794 |
0.0551 | 3.0 | 3282 | 0.0459 | 0.9868 |
0.0424 | 4.0 | 4376 | 0.0420 | 0.99 |
0.0309 | 5.0 | 5470 | 0.0393 | 0.9892 |
0.0241 | 6.0 | 6564 | 0.0417 | 0.9916 |
0.0166 | 7.0 | 7658 | 0.0419 | 0.9908 |
0.013 | 8.0 | 8752 | 0.0439 | 0.9908 |
0.0095 | 9.0 | 9846 | 0.0335 | 0.995 |
0.0068 | 10.0 | 10940 | 0.0355 | 0.994 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3