Article_250v6_NER_Model_3Epochs_UNAUGMENTED
This model is a fine-tuned version of bert-base-cased on the article250v6_wikigold_split dataset. It achieves the following results on the evaluation set:
- Loss: 0.3052
- Precision: 0.3970
- Recall: 0.3699
- F1: 0.3830
- Accuracy: 0.8863
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 |
---|---|---|---|---|---|---|---|
No log | 1.0 | 29 | 0.5222 | 0.1785 | 0.0817 | 0.1121 | 0.8202 |
No log | 2.0 | 58 | 0.3356 | 0.3575 | 0.3357 | 0.3462 | 0.8780 |
No log | 3.0 | 87 | 0.3052 | 0.3970 | 0.3699 | 0.3830 | 0.8863 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.4.0
- Tokenizers 0.11.6
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Evaluation results
- Precision on article250v6_wikigold_splitself-reported0.397
- Recall on article250v6_wikigold_splitself-reported0.370
- F1 on article250v6_wikigold_splitself-reported0.383
- Accuracy on article250v6_wikigold_splitself-reported0.886