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ner-bio-1
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: 0.3706
- Precision: 0.8569
- Recall: 0.8603
- F1: 0.8586
- Accuracy: 0.8803
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
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 240 | 0.6566 | 0.6683 | 0.7443 | 0.7043 | 0.7790 |
No log | 2.0 | 480 | 0.4004 | 0.8227 | 0.8461 | 0.8342 | 0.8680 |
0.9843 | 3.0 | 720 | 0.3706 | 0.8569 | 0.8603 | 0.8586 | 0.8803 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cpu
- Datasets 2.1.0
- Tokenizers 0.13.3