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MixGPT2_10K_fromB_BFall_20KGen_topP_0.75_noaddedB
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0642
- Accuracy: 0.9943
- F1: 0.9367
- Precision: 0.9968
- Recall: 0.8834
- Roc Auc Score: 0.9416
- Tpr At Fpr 0.01: 0.8766
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: 5.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Roc Auc Score | Tpr At Fpr 0.01 |
|---|---|---|---|---|---|---|---|---|---|
| 0.0121 | 1.0 | 7188 | 0.0325 | 0.9929 | 0.9206 | 0.9906 | 0.8598 | 0.9297 | 0.7518 |
| 0.0047 | 2.0 | 14376 | 0.0269 | 0.9943 | 0.9365 | 0.9962 | 0.8836 | 0.9417 | 0.8458 |
| 0.0032 | 3.0 | 21564 | 0.0412 | 0.9945 | 0.9385 | 0.9944 | 0.8886 | 0.9442 | 0.8502 |
| 0.0004 | 4.0 | 28752 | 0.0586 | 0.9938 | 0.9301 | 0.9966 | 0.872 | 0.9359 | 0.8558 |
| 0.0003 | 5.0 | 35940 | 0.0642 | 0.9943 | 0.9367 | 0.9968 | 0.8834 | 0.9416 | 0.8766 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.9.0+cu111
- Datasets 2.10.1
- Tokenizers 0.13.2
