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NLP-TokenClass-NER
This model is a fine-tuned version of bert-base-cased on the wikiann dataset. It achieves the following results on the evaluation set:
- Loss: 0.3741
- Precision: 0.8120
- Recall: 0.8425
- F1: 0.8269
- Accuracy: 0.9255
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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0902 | 1.0 | 2500 | 0.3741 | 0.8120 | 0.8425 | 0.8269 | 0.9255 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
