IceBERT-finetuned-ner
This model is a fine-tuned version of vesteinn/IceBERT on the mim_gold_ner dataset. It achieves the following results on the evaluation set:
- Loss: 0.0772
- Precision: 0.8920
- Recall: 0.8656
- F1: 0.8786
- Accuracy: 0.9855
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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0519 | 1.0 | 2904 | 0.0731 | 0.8700 | 0.8564 | 0.8631 | 0.9832 |
0.026 | 2.0 | 5808 | 0.0749 | 0.8771 | 0.8540 | 0.8654 | 0.9840 |
0.0159 | 3.0 | 8712 | 0.0772 | 0.8920 | 0.8656 | 0.8786 | 0.9855 |
Framework versions
- Transformers 4.11.2
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3
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Evaluation results
- Precision on mim_gold_nerself-reported0.892
- Recall on mim_gold_nerself-reported0.866
- F1 on mim_gold_nerself-reported0.879
- Accuracy on mim_gold_nerself-reported0.986