bert-base-finetuned-code-classification-major

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

• Loss: 0.1591
• Accuracy: 0.9557
• F1: 0.9555

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
0.2098	1.0	4931	0.1662	0.9522	0.9519
0.1281	2.0	9862	0.1591	0.9557	0.9555

Framework versions

• Transformers 4.28.1
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.13.3