peft-modernbert-base

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

• Loss: 0.0410
• Accuracy: 0.9887
• Matthews Correlation: 0.9850
• F1: 0.9760
• Precision: 0.9730
• Recall: 0.9792

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: 0.0001
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Matthews Correlation	F1	Precision	Recall
0.5348	0.1977	1400	0.0968	0.9722	0.9631	0.9568	0.9528	0.9609
0.2975	0.3954	2800	0.0728	0.9808	0.9745	0.9637	0.9559	0.9725
0.2385	0.5931	4200	0.0518	0.9865	0.9821	0.9731	0.9685	0.9780
0.2500	0.7908	5600	0.0443	0.9882	0.9843	0.9752	0.9709	0.9803
0.1968	0.9885	7000	0.0410	0.9887	0.9850	0.9760	0.9730	0.9792

Framework versions

• PEFT 0.18.1
• Transformers 5.2.0
• Pytorch 2.10.0+cu128
• Datasets 4.0.0
• Tokenizers 0.22.2