niaAbs_classifier

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

• Loss: 0.7958
• Accuracy: 0.8492
• F1: 0.8480
• Precision: 0.8472
• Recall: 0.8492
• Auroc: None

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: 128
• eval_batch_size: 128
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Framework versions

• Transformers 4.41.2
• Pytorch 2.5.1+cu124
• Datasets 2.20.0
• Tokenizers 0.19.1