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: 0.0807
- Precision: 0.8927
- Recall: 0.8632
- F1: 0.8777
- Accuracy: 0.9850
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 |
|---|---|---|---|---|---|---|---|
| 0.0544 | 1.0 | 2904 | 0.0774 | 0.8859 | 0.8490 | 0.8670 | 0.9833 |
| 0.0284 | 2.0 | 5808 | 0.0781 | 0.8709 | 0.8590 | 0.8649 | 0.9840 |
| 0.0166 | 3.0 | 8712 | 0.0807 | 0.8927 | 0.8632 | 0.8777 | 0.9850 |
Framework versions
- Transformers 4.11.2
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3