bert-base-finetuned-code-classification-sub

This model is a fine-tuned version of klue/bert-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.2428
• Accuracy: 0.9388
• F1: 0.9363

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.3823	1.0	4931	0.2608	0.9334	0.9301
0.214	2.0	9862	0.2428	0.9388	0.9363

Framework versions

• Transformers 4.28.1
• Pytorch 2.1.0+cu118
• Tokenizers 0.13.3