kcbert-base-finetuned-code-classification-mid

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

• Loss: 0.2025
• Accuracy: 0.9485
• F1: 0.9474

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
0.2959	1.0	4931	0.2158	0.9442	0.9428
0.1656	2.0	9862	0.2025	0.9485	0.9474

Framework versions

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