curse_classification

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

• Loss: 0.2780
• Precision: 0.8727
• Recall: 0.8752
• F1: 0.8739
• Accuracy: 0.8835

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: 128
• 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	Precision	Recall	F1	Accuracy
0.3511	1.0	618	0.2939	0.8532	0.8591	0.8561	0.8720
0.2546	2.0	1236	0.2924	0.8721	0.8552	0.8636	0.8802

Framework versions

• Transformers 4.42.3
• Pytorch 2.3.0+cu121
• Datasets 2.18.0
• Tokenizers 0.19.1