bert-finetuned-ner-ime
This model is a fine-tuned version of snunlp/KR-BERT-char16424 on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0076
- Precision: 0.9982
- Recall: 0.9982
- F1: 0.9982
- Accuracy: 0.9980
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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0378 | 1.0 | 1756 | 0.0290 | 0.9934 | 0.9939 | 0.9936 | 0.9920 |
0.0214 | 2.0 | 3512 | 0.0138 | 0.9969 | 0.9970 | 0.9970 | 0.9965 |
0.0151 | 3.0 | 5268 | 0.0076 | 0.9982 | 0.9982 | 0.9982 | 0.9980 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.11.0
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Dataset used to train jujbob/bert-finetuned-ner-ime
Evaluation results
- Precision on conll2003self-reported0.998
- Recall on conll2003self-reported0.998
- F1 on conll2003self-reported0.998
- Accuracy on conll2003self-reported0.998