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bert_human
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: 0.0451
- Accuracy: 0.9930
- F1: 0.9930
- Precision: 0.9923
- Recall: 0.9921
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.062 | 1.0 | 5488 | 0.0409 | 0.9914 | 0.9914 | 0.9924 | 0.9885 |
| 0.0279 | 2.0 | 10976 | 0.0414 | 0.9925 | 0.9925 | 0.9923 | 0.9909 |
| 0.008 | 3.0 | 16464 | 0.0451 | 0.9930 | 0.9930 | 0.9923 | 0.9921 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
