pii_mini
This model is a fine-tuned version of google/bert_uncased_L-8_H-512_A-8 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1113
- Precision: 0.9001
- Recall: 0.9290
- F1: 0.9143
- Accuracy: 0.9645
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: 3e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 153 | 0.3797 | 0.4943 | 0.5523 | 0.5217 | 0.9024 |
No log | 2.0 | 306 | 0.1868 | 0.7281 | 0.7917 | 0.7586 | 0.9419 |
No log | 3.0 | 459 | 0.1319 | 0.8339 | 0.8735 | 0.8532 | 0.9565 |
0.5069 | 4.0 | 612 | 0.1098 | 0.8690 | 0.8990 | 0.8837 | 0.9603 |
0.5069 | 5.0 | 765 | 0.0971 | 0.8725 | 0.9082 | 0.8900 | 0.9647 |
0.5069 | 6.0 | 918 | 0.0924 | 0.8887 | 0.9179 | 0.9031 | 0.9653 |
0.1032 | 7.0 | 1071 | 0.0920 | 0.8820 | 0.9175 | 0.8994 | 0.9632 |
0.1032 | 8.0 | 1224 | 0.0869 | 0.8886 | 0.9219 | 0.9050 | 0.9652 |
0.1032 | 9.0 | 1377 | 0.0912 | 0.8917 | 0.9235 | 0.9073 | 0.9649 |
0.0719 | 10.0 | 1530 | 0.0875 | 0.8995 | 0.9271 | 0.9131 | 0.9666 |
0.0719 | 11.0 | 1683 | 0.0964 | 0.8971 | 0.9264 | 0.9115 | 0.9649 |
0.0719 | 12.0 | 1836 | 0.1006 | 0.9030 | 0.9293 | 0.9159 | 0.9656 |
0.0719 | 13.0 | 1989 | 0.1011 | 0.8978 | 0.9291 | 0.9132 | 0.9639 |
0.0539 | 14.0 | 2142 | 0.1071 | 0.9007 | 0.9275 | 0.9139 | 0.9628 |
0.0539 | 15.0 | 2295 | 0.1113 | 0.9001 | 0.9290 | 0.9143 | 0.9645 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.1
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