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MixGPT2_10K_fromB_BFall_40KGen_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: 0.0427
- Accuracy: 0.9953
- F1: 0.9488
- Precision: 0.9956
- Recall: 0.9062
- Roc Auc Score: 0.9530
- Tpr At Fpr 0.01: 0.8878
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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.014 | 1.0 | 7813 | 0.0293 | 0.9945 | 0.9402 | 0.9761 | 0.9068 | 0.9528 | 0.0 |
| 0.0053 | 2.0 | 15626 | 0.0322 | 0.9942 | 0.9360 | 0.9893 | 0.8882 | 0.9439 | 0.8134 |
| 0.0032 | 3.0 | 23439 | 0.0360 | 0.9953 | 0.9487 | 0.9924 | 0.9088 | 0.9542 | 0.8634 |
| 0.0 | 4.0 | 31252 | 0.0522 | 0.9940 | 0.9325 | 0.9975 | 0.8754 | 0.9376 | 0.8722 |
| 0.0 | 5.0 | 39065 | 0.0427 | 0.9953 | 0.9488 | 0.9956 | 0.9062 | 0.9530 | 0.8878 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.9.0+cu111
- Datasets 2.10.1
- Tokenizers 0.13.2
