bert-finetuned-ner
This model is a fine-tuned version of bert-base-cased on the conll2003 dataset.
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
- training_steps: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 0.0285 | 50 | 0.6677 | 0.0925 | 0.0219 | 0.0354 | 0.7927 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cpu
- Datasets 2.12.0
- Tokenizers 0.19.1
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Model tree for scmis011/bert-finetuned-ner
Base model
google-bert/bert-base-cased