Hal_mdeberta-v3-base_finetuned

This model is a fine-tuned version of microsoft/mdeberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.8589
• Accuracy: 0.7579
• F1: {'f1': 0.7578571428571429}

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: 20
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6522	1.0	700	0.6837	0.7436	{'f1': 0.7435714285714285}
0.6644	2.0	1400	0.6963	0.7507	{'f1': 0.7507142857142857}
0.5929	3.0	2100	0.7551	0.7414	{'f1': 0.7414285714285715}
0.4483	4.0	2800	0.8589	0.7579	{'f1': 0.7578571428571429}
0.3686	5.0	3500	1.2816	0.7293	{'f1': 0.7292857142857143}
0.3264	6.0	4200	1.2971	0.7357	{'f1': 0.7357142857142858}
0.1958	7.0	4900	1.3579	0.7507	{'f1': 0.7507142857142857}

Framework versions

• Transformers 4.48.0
• Pytorch 2.6.0+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0