modernbert-3pairs-grande

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

• Loss: 0.0797
• Accuracy: 0.9707
• F1: 0.9707
• Precision: 0.9707
• Recall: 0.9707
• F1 Class 0: 0.9706
• Precision Class 0: 0.9742
• Recall Class 0: 0.9670
• F1 Class 1: 0.9708
• Precision Class 1: 0.9672
• Recall Class 1: 0.9744

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: 1e-05
• train_batch_size: 128
• eval_batch_size: 128
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• total_train_batch_size: 1024
• total_eval_batch_size: 1024
• 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: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	F1 Class 0	Precision Class 0	Recall Class 0	F1 Class 1	Precision Class 1	Recall Class 1
0.6549	1.0	1701	0.0797	0.9707	0.9707	0.9707	0.9707	0.9706	0.9742	0.9670	0.9708	0.9672	0.9744

Framework versions

• Transformers 4.55.0
• Pytorch 2.8.0+cu128
• Datasets 4.0.0
• Tokenizers 0.21.4