kcbert-large-finetuned-nsmc

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

• Loss: 0.2576
• Accuracy: 0.9137
• F1: 0.9137

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
0.267	1.0	3750	0.2231	0.9106	0.9106
0.1427	2.0	7500	0.2576	0.9137	0.9137

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.0