klue-ner-koelectra

This model is a fine-tuned version of monologg/koelectra-base-v3-discriminator on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.9249
• Dt: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 19}
• Lc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17}
• Og: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 23}
• Ps: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 47}
• Qt: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 50}
• Ti: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 7}
• Overall Precision: 0.0
• Overall Recall: 0.0
• Overall F1: 0.0
• Overall Accuracy: 0.7639

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Dt	Lc	Og	Ps	Qt	Ti	Overall Precision	Overall Recall	Overall F1	Overall Accuracy
No log	1.0	32	1.0989	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 19}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 23}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 47}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 50}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 7}	0.0	0.0	0.0	0.7639
No log	2.0	64	0.9698	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 19}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 23}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 47}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 50}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 7}	0.0	0.0	0.0	0.7639
No log	3.0	96	0.9249	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 19}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 23}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 47}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 50}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 7}	0.0	0.0	0.0	0.7639

Framework versions

• Transformers 4.52.4
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.1