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modernbert-pii-mapped-v8
jefftherover/modernbert-pii-mapped-v8
modernbert-pii-mapped-v8 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-0ef3e9" 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 30, 2026
- Updated
- May 30, 2026
- SHA
- e2238aa2
Try a prompt
Base models
Model card
From the Hugging Face model README
<a href="https://huggingface.co/spaces/jefftherover/huggingface-static-0ef3e9" 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-v8
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: 0.0128
- Precision: 0.9482
- Recall: 0.9583
- F1: 0.9532
- Accuracy: 0.9965
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 |
|---|---|---|---|---|---|---|---|
| 0.0677 | 0.4087 | 500 | 0.0285 | 0.8815 | 0.9724 | 0.9247 | 0.9913 |
| 0.0359 | 0.8173 | 1000 | 0.0150 | 0.9371 | 0.9710 | 0.9538 | 0.9957 |
| 0.0200 | 1.2256 | 1500 | 0.0127 | 0.9476 | 0.9846 | 0.9658 | 0.9965 |
| 0.0168 | 1.6342 | 2000 | 0.0109 | 0.9422 | 0.9741 | 0.9579 | 0.9965 |
| 0.0135 | 2.0425 | 2500 | 0.0096 | 0.9560 | 0.9695 | 0.9627 | 0.9971 |
| 0.0067 | 2.4512 | 3000 | 0.0128 | 0.9482 | 0.9583 | 0.9532 | 0.9965 |
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 30, 2026
- Updated
- May 30, 2026