output_jcommonsenseqa

This model is a fine-tuned version of cl-tohoku/bert-base-japanese-v3 on the jglue dataset. It achieves the following results on the evaluation set:

• Loss: 0.5267
• Accuracy: 0.8302

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.231	1.0	280	0.5796	0.8239
0.3484	2.0	560	0.4979	0.8239
0.2421	3.0	840	0.5267	0.8302

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0