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