bert-japanese-ner
This model is a fine-tuned version of cl-tohoku/bert-base-japanese-whole-word-masking on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0842
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: 5e-05
- train_batch_size: 24
- eval_batch_size: 24
- 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 |
|---|---|---|---|
| 0.2834 | 1.0 | 179 | 0.0915 |
| 0.0548 | 2.0 | 358 | 0.0831 |
| 0.0235 | 3.0 | 537 | 0.0842 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.12.1.post201
- Datasets 2.12.0
- Tokenizers 0.13.3