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modernbert-pii-mapped-v10
jefftherover/modernbert-pii-mapped-v10
modernbert-pii-mapped-v10 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
- 8f076fc7
Try a prompt
Base models
Model card
From the Hugging Face model README
<a href="https://huggingface.co/spaces/jefftherover/huggingface-static-d59ed0" 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-v10
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: 0.9759
- Recall: 0.9896
- F1: 0.9827
- Accuracy: 0.9981
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 |
|---|---|---|---|---|---|---|---|
| 0.0641 | 0.3591 | 500 | 0.0299 | 0.8870 | 0.9455 | 0.9153 | 0.9914 |
| 0.0396 | 0.7181 | 1000 | 0.0148 | 0.9440 | 0.9813 | 0.9623 | 0.9955 |
| 0.0178 | 1.0768 | 1500 | 0.0098 | 0.9615 | 0.9864 | 0.9738 | 0.9970 |
| 0.0154 | 1.4359 | 2000 | 0.0120 | 0.9617 | 0.9905 | 0.9759 | 0.9967 |
| 0.0156 | 1.7950 | 2500 | 0.0096 | 0.9615 | 0.9811 | 0.9712 | 0.9970 |
| 0.0064 | 2.1537 | 3000 | 0.0080 | 0.9707 | 0.9924 | 0.9814 | 0.9976 |
| 0.0063 | 2.5127 | 3500 | 0.0070 | 0.9749 | 0.9937 | 0.9842 | 0.9979 |
| 0.0081 | 2.8718 | 4000 | 0.0072 | 0.9737 | 0.9902 | 0.9819 | 0.9980 |
| 0.0020 | 3.2305 | 4500 | 0.0071 | 0.9762 | 0.9931 | 0.9846 | 0.9981 |
| 0.0036 | 3.5896 | 5000 | 0.0075 | 0.9739 | 0.9890 | 0.9814 | 0.9980 |
| 0.0018 | 3.9487 | 5500 | 0.0074 | 0.9747 | 0.9856 | 0.9801 | 0.9980 |
| 0.0007 | 4.3074 | 6000 | 0.0077 | 0.9759 | 0.9896 | 0.9827 | 0.9981 |
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