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DistilRoBERTa_PKDD-Anomaly_Baseline
This model is a fine-tuned version of distilroberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4357
- Accuracy: 0.8526
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 |
---|---|---|---|---|
0.5987 | 1.0 | 1094 | 0.5785 | 0.6988 |
0.5596 | 2.0 | 2188 | 0.5399 | 0.7422 |
0.5235 | 3.0 | 3282 | 0.5047 | 0.785 |
0.4967 | 4.0 | 4376 | 0.4834 | 0.8202 |
0.4783 | 5.0 | 5470 | 0.4628 | 0.8318 |
0.4649 | 6.0 | 6564 | 0.4513 | 0.839 |
0.4599 | 7.0 | 7658 | 0.4442 | 0.8438 |
0.4534 | 8.0 | 8752 | 0.4371 | 0.8458 |
0.4508 | 9.0 | 9846 | 0.4401 | 0.8464 |
0.4473 | 10.0 | 10940 | 0.4359 | 0.846 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3