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GPTNEO_CSIC-Anomaly_Baseline
This model is a fine-tuned version of EleutherAI/gpt-neo-1.3B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6018
- Accuracy: 0.6693
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.7146 | 1.0 | 2187 | 0.6458 | 0.6366 |
| 0.6328 | 2.0 | 4375 | 0.6275 | 0.658 |
| 0.6219 | 3.0 | 6562 | 0.6180 | 0.6572 |
| 0.6111 | 4.0 | 8750 | 0.6115 | 0.6632 |
| 0.6087 | 5.0 | 10937 | 0.6064 | 0.6658 |
| 0.6026 | 6.0 | 13125 | 0.6036 | 0.6714 |
| 0.5998 | 7.0 | 15312 | 0.6014 | 0.6664 |
| 0.5996 | 8.0 | 17500 | 0.6018 | 0.6768 |
| 0.5949 | 9.0 | 19687 | 0.5994 | 0.6758 |
| 0.596 | 10.0 | 21870 | 0.5986 | 0.6766 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
