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pii-layout-synth-v4
jefftherover/pii-layout-synth-v4
pii-layout-synth-v4 is a token classification model from jefftherover. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- modernbert
- Access
- Public
- Created
- Jun 12, 2026
- Updated
- Jun 12, 2026
- SHA
- 7f495322
Try a prompt
Base models
Model card
From the Hugging Face model README
<a href="https://huggingface.co/spaces/jefftherover/huggingface-static-349edf" target="_blank"><img src="https://raw.githubusercontent.com/gradio-app/trackio/refs/heads/main/trackio/assets/badge.png" alt="Visualize in Trackio" title="Visualize in Trackio" style="height: 40px;"/></a>
<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->pii-layout-synth-v4
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: 0.0049
- Precision: 0.9906
- Recall: 0.9940
- 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: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1117 | 0.2389 | 500 | 0.0483 | 0.8936 | 0.9383 | 0.9154 | 0.9859 |
| 0.0453 | 0.4778 | 1000 | 0.0176 | 0.9594 | 0.9769 | 0.9681 | 0.9947 |
| 0.0294 | 0.7167 | 1500 | 0.0111 | 0.9749 | 0.9877 | 0.9813 | 0.9968 |
| 0.0157 | 0.9556 | 2000 | 0.0089 | 0.9774 | 0.9886 | 0.9830 | 0.9970 |
| 0.0126 | 1.1945 | 2500 | 0.0072 | 0.9835 | 0.9896 | 0.9866 | 0.9978 |
| 0.0098 | 1.4333 | 3000 | 0.0064 | 0.9854 | 0.9920 | 0.9886 | 0.9980 |
| 0.0097 | 1.6722 | 3500 | 0.0053 | 0.9877 | 0.9936 | 0.9906 | 0.9983 |
| 0.0088 | 1.9111 | 4000 | 0.0056 | 0.9868 | 0.9916 | 0.9892 | 0.9982 |
| 0.0057 | 2.1500 | 4500 | 0.0057 | 0.9882 | 0.9921 | 0.9901 | 0.9983 |
| 0.0049 | 2.3889 | 5000 | 0.0055 | 0.9887 | 0.9936 | 0.9911 | 0.9984 |
| 0.0057 | 2.6278 | 5500 | 0.0052 | 0.9898 | 0.9946 | 0.9922 | 0.9985 |
| 0.0050 | 2.8667 | 6000 | 0.0052 | 0.9888 | 0.9932 | 0.9910 | 0.9984 |
| 0.0018 | 3.1056 | 6500 | 0.0051 | 0.9910 | 0.9946 | 0.9928 | 0.9986 |
| 0.0025 | 3.3445 | 7000 | 0.0051 | 0.9903 | 0.9950 | 0.9927 | 0.9986 |
| 0.0018 | 3.5834 | 7500 | 0.0053 | 0.9912 | 0.9939 | 0.9925 | 0.9986 |
| 0.0020 | 3.8223 | 8000 | 0.0049 | 0.9906 | 0.9940 | 0.9923 | 0.9986 |
Framework versions
- Transformers 5.11.0
- Pytorch 2.12.0+cu130
- Datasets 5.0.0
- Tokenizers 0.22.2
- Task
- Token Classification
- Library
- transformers
- Type
- modernbert
- License
- apache-2.0
- Created
- Jun 12, 2026
- Updated
- Jun 12, 2026