roberta-base-klue-ynat-classification

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

• Loss: 1.1490
• 정확도: 0.82

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	정확도
No log	1.0	125	0.9073	0.82
No log	2.0	250	0.9611	0.82
No log	3.0	375	0.9956	0.83

Framework versions

• Transformers 4.40.1
• Pytorch 2.5.0+cu118
• Datasets 2.19.0
• Tokenizers 0.19.1