pii-layout-synth-v13

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: 0.0050
• Precision: 0.9902
• Recall: 0.9943
• F1: 0.9923
• Accuracy: 0.9986

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: 5e-05
• train_batch_size: 16
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 2
• 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: cosine_with_restarts
• lr_scheduler_warmup_steps: 200
• num_epochs: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0141	0.9818	2000	0.0074	0.9806	0.9857	0.9832	0.9975
0.0078	1.9637	4000	0.0050	0.9889	0.9945	0.9917	0.9984
0.0029	2.9455	6000	0.0045	0.9903	0.9950	0.9926	0.9986
0.0009	3.9273	8000	0.0050	0.9902	0.9943	0.9922	0.9986
0.0009	4.0	8148	0.0050	0.9902	0.9943	0.9923	0.9986

Framework versions

• Transformers 5.12.1
• Pytorch 2.12.1+cu130
• Datasets 5.0.0
• Tokenizers 0.22.2