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bert-finetuned-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: 0.5677
- Precision: 0.3452
- Recall: 0.5421
- F1: 0.4218
- Accuracy: 0.8688
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 13 | 0.5728 | 0.2077 | 0.3551 | 0.2621 | 0.8199 |
| No log | 2.0 | 26 | 0.5687 | 0.2889 | 0.3645 | 0.3223 | 0.8312 |
| No log | 3.0 | 39 | 0.5447 | 0.2857 | 0.4486 | 0.3491 | 0.8425 |
| No log | 4.0 | 52 | 0.5509 | 0.2881 | 0.4766 | 0.3592 | 0.8489 |
| No log | 5.0 | 65 | 0.5751 | 0.3121 | 0.4579 | 0.3712 | 0.8511 |
| No log | 6.0 | 78 | 0.5358 | 0.3851 | 0.5794 | 0.4627 | 0.8667 |
| No log | 7.0 | 91 | 0.5484 | 0.3491 | 0.5514 | 0.4275 | 0.8645 |
| No log | 8.0 | 104 | 0.5671 | 0.3580 | 0.5421 | 0.4312 | 0.8672 |
| No log | 9.0 | 117 | 0.5666 | 0.3494 | 0.5421 | 0.4249 | 0.8688 |
| No log | 10.0 | 130 | 0.5677 | 0.3452 | 0.5421 | 0.4218 | 0.8688 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
