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modernbert-pii-mapped-v11
jefftherover/modernbert-pii-mapped-v11
modernbert-pii-mapped-v11 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
- May 31, 2026
- Updated
- May 31, 2026
- SHA
- 11d47276
Try a prompt
Base models
Model card
From the Hugging Face model README
<a href="https://huggingface.co/spaces/jefftherover/huggingface-static-6d2a03" 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. -->modernbert-pii-mapped-v11
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: 0.0085
- Precision: 0.9779
- Recall: 0.9894
- F1: 0.9836
- Accuracy: 0.9982
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 |
|---|---|---|---|---|---|---|---|
| 0.0729 | 0.3591 | 500 | 0.0400 | 0.8604 | 0.9370 | 0.8970 | 0.9889 |
| 0.0413 | 0.7181 | 1000 | 0.0143 | 0.9426 | 0.9709 | 0.9566 | 0.9956 |
| 0.0169 | 1.0768 | 1500 | 0.0108 | 0.9605 | 0.9868 | 0.9735 | 0.9968 |
| 0.0133 | 1.4359 | 2000 | 0.0086 | 0.9671 | 0.9903 | 0.9785 | 0.9974 |
| 0.0163 | 1.7950 | 2500 | 0.0098 | 0.9614 | 0.9778 | 0.9695 | 0.9968 |
| 0.0079 | 2.1537 | 3000 | 0.0099 | 0.9668 | 0.9880 | 0.9773 | 0.9971 |
| 0.0057 | 2.5127 | 3500 | 0.0077 | 0.9757 | 0.9912 | 0.9833 | 0.9979 |
| 0.0076 | 2.8718 | 4000 | 0.0085 | 0.9700 | 0.9868 | 0.9783 | 0.9976 |
| 0.0020 | 3.2305 | 4500 | 0.0074 | 0.9771 | 0.9905 | 0.9838 | 0.9982 |
| 0.0018 | 3.5896 | 5000 | 0.0077 | 0.9774 | 0.9900 | 0.9837 | 0.9982 |
| 0.0016 | 3.9487 | 5500 | 0.0079 | 0.9772 | 0.9884 | 0.9828 | 0.9982 |
| 0.0007 | 4.3074 | 6000 | 0.0084 | 0.9781 | 0.9916 | 0.9848 | 0.9982 |
| 0.0004 | 4.6664 | 6500 | 0.0085 | 0.9783 | 0.9889 | 0.9836 | 0.9982 |
| 0.0011 | 5.0 | 6965 | 0.0085 | 0.9779 | 0.9894 | 0.9836 | 0.9982 |
Framework versions
- Transformers 5.9.0
- Pytorch 2.12.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2
- Task
- Token Classification
- Library
- transformers
- Type
- modernbert
- License
- apache-2.0
- Created
- May 31, 2026
- Updated
- May 31, 2026