label_4_Test

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

• Loss: 0.0461
• Accuracy: 0.9899

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: 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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	99	0.0693	0.9798
No log	2.0	198	0.0522	0.9798
No log	3.0	297	0.0581	0.9697
No log	4.0	396	0.0394	0.9899
No log	5.0	495	0.0367	0.9899
0.1504	6.0	594	0.0506	0.9899
0.1504	7.0	693	0.0402	0.9899
0.1504	8.0	792	0.0476	0.9899
0.1504	9.0	891	0.0453	0.9899
0.1504	10.0	990	0.0461	0.9899

Framework versions

• Transformers 4.39.3
• Pytorch 2.2.2+cu121
• Datasets 2.19.0
• Tokenizers 0.15.2