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GPT2_CSIC-Anomaly
This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0155
- Accuracy: 0.9961
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
- gradient_accumulation_steps: 10
- total_train_batch_size: 80
- 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 |
|---|---|---|---|---|
| 0.3352 | 1.0 | 437 | 0.1213 | 0.955 |
| 0.0807 | 2.0 | 875 | 0.0584 | 0.9844 |
| 0.0483 | 3.0 | 1312 | 0.0370 | 0.9894 |
| 0.0314 | 4.0 | 1750 | 0.0282 | 0.991 |
| 0.0252 | 5.0 | 2187 | 0.0269 | 0.9932 |
| 0.0204 | 6.0 | 2625 | 0.0233 | 0.9942 |
| 0.0169 | 7.0 | 3062 | 0.0261 | 0.9934 |
| 0.0138 | 8.0 | 3500 | 0.0187 | 0.9948 |
| 0.0114 | 9.0 | 3937 | 0.0178 | 0.9962 |
| 0.0102 | 9.99 | 4370 | 0.0166 | 0.996 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
