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pii-layout-synth-v1
jefftherover/pii-layout-synth-v1
pii-layout-synth-v1 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
- Jun 10, 2026
- Updated
- Jun 10, 2026
- SHA
- bb34869b
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Base models
Model card
From the Hugging Face model README
<a href="https://huggingface.co/spaces/jefftherover/huggingface-static-b842a7" 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. -->pii-layout-synth-v1
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: 0.0040
- Precision: 0.9934
- Recall: 0.9956
- F1: 0.9945
- Accuracy: 0.9991
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 |
|---|---|---|---|---|---|---|---|
| 0.0666 | 0.2386 | 500 | 0.0279 | 0.9352 | 0.9544 | 0.9447 | 0.9922 |
| 0.0305 | 0.4772 | 1000 | 0.0174 | 0.9665 | 0.9808 | 0.9736 | 0.9955 |
| 0.0172 | 0.7158 | 1500 | 0.0101 | 0.9743 | 0.9825 | 0.9784 | 0.9970 |
| 0.0197 | 0.9544 | 2000 | 0.0056 | 0.9856 | 0.9908 | 0.9882 | 0.9984 |
| 0.0064 | 1.1928 | 2500 | 0.0057 | 0.9880 | 0.9916 | 0.9898 | 0.9985 |
| 0.0080 | 1.4314 | 3000 | 0.0049 | 0.9879 | 0.9928 | 0.9903 | 0.9986 |
| 0.0076 | 1.6700 | 3500 | 0.0050 | 0.9878 | 0.9899 | 0.9888 | 0.9985 |
| 0.0078 | 1.9086 | 4000 | 0.0042 | 0.9916 | 0.9943 | 0.9930 | 0.9989 |
| 0.0035 | 2.1470 | 4500 | 0.0038 | 0.9913 | 0.9941 | 0.9927 | 0.9989 |
| 0.0031 | 2.3856 | 5000 | 0.0038 | 0.9911 | 0.9938 | 0.9924 | 0.9989 |
| 0.0026 | 2.6242 | 5500 | 0.0037 | 0.9921 | 0.9948 | 0.9935 | 0.9990 |
| 0.0021 | 2.8628 | 6000 | 0.0042 | 0.9920 | 0.9949 | 0.9934 | 0.9989 |
| 0.0011 | 3.1012 | 6500 | 0.0037 | 0.9927 | 0.9951 | 0.9939 | 0.9991 |
| 0.0012 | 3.3398 | 7000 | 0.0040 | 0.9927 | 0.9950 | 0.9938 | 0.9991 |
| 0.0009 | 3.5784 | 7500 | 0.0039 | 0.9930 | 0.9952 | 0.9941 | 0.9991 |
| 0.0009 | 3.8170 | 8000 | 0.0038 | 0.9936 | 0.9959 | 0.9948 | 0.9991 |
| 0.0003 | 4.0554 | 8500 | 0.0039 | 0.9935 | 0.9955 | 0.9945 | 0.9991 |
| 0.0003 | 4.2940 | 9000 | 0.0040 | 0.9934 | 0.9955 | 0.9945 | 0.9991 |
| 0.0001 | 4.5326 | 9500 | 0.0040 | 0.9934 | 0.9956 | 0.9945 | 0.9991 |
Framework versions
- Transformers 5.10.2
- Pytorch 2.12.0+cu130
- Datasets 5.0.0
- Tokenizers 0.22.2
- Task
- Token Classification
- Library
- transformers
- Type
- modernbert
- License
- apache-2.0
- Created
- Jun 10, 2026
- Updated
- Jun 10, 2026