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modernbert-pii-mapped-v12
jefftherover/modernbert-pii-mapped-v12
modernbert-pii-mapped-v12 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.
<a href="https://huggingface.co/spaces/jefftherover/huggingface-static-31b720" target="blank"<img src="https://raw.githubusercontent.com/gradio-app/trackio/refs/heads/main/trackio/assets/badge.png" alt="Visualize in T…
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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
- dff55dae
Try a prompt
Base models
Model card
From the Hugging Face model README
<a href="https://huggingface.co/spaces/jefftherover/huggingface-static-31b720" 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-v12
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: 0.0077
- Precision: 0.9787
- Recall: 0.9909
- F1: 0.9848
- 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 |
|---|---|---|---|---|---|---|---|
| 0.0656 | 0.3591 | 500 | 0.0333 | 0.8816 | 0.9458 | 0.9125 | 0.9910 |
| 0.0408 | 0.7181 | 1000 | 0.0189 | 0.9444 | 0.9723 | 0.9582 | 0.9949 |
| 0.0156 | 1.0768 | 1500 | 0.0099 | 0.9639 | 0.9865 | 0.9751 | 0.9969 |
| 0.0136 | 1.4359 | 2000 | 0.0104 | 0.9695 | 0.9935 | 0.9814 | 0.9972 |
| 0.0163 | 1.7950 | 2500 | 0.0094 | 0.9617 | 0.9769 | 0.9692 | 0.9969 |
| 0.0061 | 2.1537 | 3000 | 0.0080 | 0.9728 | 0.9917 | 0.9822 | 0.9978 |
| 0.0080 | 2.5127 | 3500 | 0.0069 | 0.9757 | 0.9935 | 0.9845 | 0.9980 |
| 0.0075 | 2.8718 | 4000 | 0.0076 | 0.9778 | 0.9917 | 0.9847 | 0.9981 |
| 0.0023 | 3.2305 | 4500 | 0.0078 | 0.9778 | 0.9929 | 0.9853 | 0.9981 |
| 0.0020 | 3.5896 | 5000 | 0.0076 | 0.9783 | 0.9916 | 0.9849 | 0.9980 |
| 0.0017 | 3.9487 | 5500 | 0.0073 | 0.9766 | 0.9890 | 0.9828 | 0.9981 |
| 0.0005 | 4.3074 | 6000 | 0.0078 | 0.9792 | 0.9925 | 0.9858 | 0.9982 |
| 0.0006 | 4.6664 | 6500 | 0.0076 | 0.9787 | 0.9906 | 0.9846 | 0.9982 |
| 0.0007 | 5.0 | 6965 | 0.0077 | 0.9787 | 0.9909 | 0.9848 | 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