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: 0.0815
- Precision: 0.8870
- Recall: 0.8576
- F1: 0.8721
- Accuracy: 0.9848
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 |
|---|---|---|---|---|---|---|---|
| 0.0536 | 1.0 | 2904 | 0.0749 | 0.8749 | 0.8426 | 0.8585 | 0.9831 |
| 0.0269 | 2.0 | 5808 | 0.0754 | 0.8734 | 0.8471 | 0.8600 | 0.9840 |
| 0.0173 | 3.0 | 8712 | 0.0815 | 0.8870 | 0.8576 | 0.8721 | 0.9848 |
Framework versions
- Transformers 4.11.0
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3
- Downloads last month
- 29
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for vesteinn/IceBERT-finetuned-ner
Base model
vesteinn/IceBERTEvaluation results
- Precision on mim_gold_nerself-reported0.887
- Recall on mim_gold_nerself-reported0.858
- F1 on mim_gold_nerself-reported0.872
- Accuracy on mim_gold_nerself-reported0.985