kobigbird-bert-base-News

This model is a fine-tuned version of monologg/kobigbird-bert-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2298
• Accuracy: 0.9367
• F1: 0.9369

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
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6302	1.0	614	0.3209	0.9037	0.9023
0.2721	2.0	1228	0.2438	0.9293	0.9298
0.1845	3.0	1842	0.2298	0.9367	0.9369

Framework versions

• Transformers 4.28.1
• Pytorch 2.1.0+cu121
• Datasets 2.15.0
• Tokenizers 0.13.3