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bert-large-cased-ft-ner-maplestory
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1738
- Precision: 0.6773
- Recall: 0.7495
- F1: 0.7116
- Accuracy: 0.9653
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: 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: 7
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0841 | 1.0 | 2948 | 0.1276 | 0.6558 | 0.7005 | 0.6774 | 0.9614 |
0.0688 | 2.0 | 5896 | 0.1390 | 0.6499 | 0.7301 | 0.6877 | 0.9615 |
0.06 | 3.0 | 8844 | 0.1332 | 0.6587 | 0.7336 | 0.6941 | 0.9630 |
0.0439 | 4.0 | 11792 | 0.1435 | 0.6783 | 0.7319 | 0.7041 | 0.9646 |
0.0295 | 5.0 | 14740 | 0.1551 | 0.6714 | 0.7355 | 0.7020 | 0.9642 |
0.0207 | 6.0 | 17688 | 0.1665 | 0.6764 | 0.7435 | 0.7084 | 0.9649 |
0.0145 | 7.0 | 20636 | 0.1738 | 0.6773 | 0.7495 | 0.7116 | 0.9653 |
Framework versions
- Transformers 4.34.1
- Pytorch 1.12.0
- Datasets 2.14.6
- Tokenizers 0.14.1