klue_bert_base

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

• Loss: 0.2415
• Accuracy: 0.9056
• F1: 0.9056

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: 64
• eval_batch_size: 64
• 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
0.2742	1.0	2344	0.2381	0.9005	0.9005
0.1865	2.0	4688	0.2415	0.9056	0.9056

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.9.0
• Tokenizers 0.13.2