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bert-finetuned-ner
This model is a fine-tuned version of lightsaber689/bert-finetuned-ner on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4704
- Precision: 0.6442
- Recall: 0.6321
- F1: 0.6381
- Accuracy: 0.9324
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: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 164 | 0.5514 | 0.4379 | 0.6321 | 0.5174 | 0.8455 |
No log | 2.0 | 328 | 0.4271 | 0.5739 | 0.6226 | 0.5973 | 0.9195 |
No log | 3.0 | 492 | 0.4892 | 0.4672 | 0.6038 | 0.5267 | 0.8862 |
0.029 | 4.0 | 656 | 0.4467 | 0.5905 | 0.5849 | 0.5877 | 0.9250 |
0.029 | 5.0 | 820 | 0.4470 | 0.5596 | 0.5755 | 0.5674 | 0.9255 |
0.029 | 6.0 | 984 | 0.4250 | 0.6117 | 0.5943 | 0.6029 | 0.9339 |
0.0207 | 7.0 | 1148 | 0.4667 | 0.6132 | 0.6132 | 0.6132 | 0.9305 |
0.0207 | 8.0 | 1312 | 0.4704 | 0.6442 | 0.6321 | 0.6381 | 0.9324 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1