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modernbert-pii-mapped-v9
jefftherover/modernbert-pii-mapped-v9
modernbert-pii-mapped-v9 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-867e22" 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
- 9e1beb01
Try a prompt
Base models
Model card
From the Hugging Face model README
<a href="https://huggingface.co/spaces/jefftherover/huggingface-static-867e22" 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-v9
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: 0.0082
- Precision: 0.9732
- Recall: 0.9868
- F1: 0.9799
- Accuracy: 0.9977
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 |
|---|---|---|---|---|---|---|---|
| 0.0770 | 0.3591 | 500 | 0.0385 | 0.8678 | 0.9505 | 0.9073 | 0.9893 |
| 0.0417 | 0.7181 | 1000 | 0.0166 | 0.9362 | 0.9773 | 0.9563 | 0.9949 |
| 0.0210 | 1.0768 | 1500 | 0.0104 | 0.9554 | 0.9816 | 0.9684 | 0.9968 |
| 0.0151 | 1.4359 | 2000 | 0.0141 | 0.9636 | 0.9861 | 0.9747 | 0.9965 |
| 0.0128 | 1.7950 | 2500 | 0.0113 | 0.9561 | 0.9745 | 0.9652 | 0.9965 |
| 0.0057 | 2.1537 | 3000 | 0.0080 | 0.9716 | 0.9947 | 0.9830 | 0.9977 |
| 0.0061 | 2.5127 | 3500 | 0.0078 | 0.9726 | 0.9934 | 0.9829 | 0.9977 |
| 0.0081 | 2.8718 | 4000 | 0.0083 | 0.9704 | 0.9879 | 0.9791 | 0.9976 |
| 0.0021 | 3.2305 | 4500 | 0.0082 | 0.9732 | 0.9868 | 0.9799 | 0.9977 |
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