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bert-token-class
This model is a fine-tuned version of dbmdz/bert-base-cased-finetuned-conll03-english on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3415
- Precision: 0.8222
- Recall: 0.7213
- F1: 0.7582
- Accuracy: 0.9047
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.2622 | 1.0 | 1796 | 0.2673 | 0.8584 | 0.6573 | 0.7051 | 0.8995 |
0.2112 | 2.0 | 3592 | 0.2666 | 0.8464 | 0.6877 | 0.7343 | 0.9037 |
0.1682 | 3.0 | 5388 | 0.2891 | 0.8336 | 0.7115 | 0.7531 | 0.9056 |
0.1302 | 4.0 | 7184 | 0.3224 | 0.8279 | 0.7133 | 0.7532 | 0.9047 |
0.1113 | 5.0 | 8980 | 0.3415 | 0.8222 | 0.7213 | 0.7582 | 0.9047 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3