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GPT2_Thuderbird-Anomaly_Baseline
This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0372
- Accuracy: 0.9864
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
- gradient_accumulation_steps: 10
- total_train_batch_size: 320
- 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 |
---|---|---|---|---|
0.3763 | 1.0 | 109 | 0.3583 | 0.9094 |
0.2193 | 1.99 | 218 | 0.2309 | 0.9278 |
0.1411 | 3.0 | 328 | 0.1515 | 0.9480 |
0.1016 | 3.99 | 437 | 0.1039 | 0.9684 |
0.0747 | 5.0 | 547 | 0.0746 | 0.9792 |
0.0576 | 6.0 | 656 | 0.0572 | 0.9828 |
0.051 | 6.99 | 765 | 0.0477 | 0.9844 |
0.0442 | 8.0 | 875 | 0.0427 | 0.9856 |
0.0412 | 8.99 | 984 | 0.0405 | 0.9866 |
0.0397 | 9.96 | 1090 | 0.0398 | 0.9868 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3