<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
bert-finetuned-ner
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2364
- Precision: 0.8092
- Recall: 0.8078
- F1: 0.8085
- Accuracy: 0.9582
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: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.1312 | 1.0 | 895 | 0.0957 | 0.8112 | 0.7853 | 0.7981 | 0.9577 |
0.0897 | 2.0 | 1790 | 0.1037 | 0.8345 | 0.7914 | 0.8124 | 0.9577 |
0.0696 | 3.0 | 2685 | 0.1083 | 0.8368 | 0.7914 | 0.8135 | 0.9579 |
0.0524 | 4.0 | 3580 | 0.1268 | 0.7835 | 0.8172 | 0.8000 | 0.9580 |
0.0451 | 5.0 | 4475 | 0.1628 | 0.7877 | 0.825 | 0.8059 | 0.9573 |
0.032 | 6.0 | 5370 | 0.1977 | 0.8002 | 0.8043 | 0.8022 | 0.9570 |
0.0231 | 7.0 | 6265 | 0.2178 | 0.8045 | 0.8052 | 0.8048 | 0.9570 |
0.0183 | 8.0 | 7160 | 0.2364 | 0.8092 | 0.8078 | 0.8085 | 0.9582 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2