| --- |
| library_name: transformers |
| license: mit |
| base_model: microsoft/deberta-v3-small |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: PII-Token-Filter-Hard-V1 |
| results: [] |
| --- |
| |
| <!-- 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-Token-Filter-Hard-V1 |
|
|
| This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.9765 |
| - Precision: 0.2376 |
| - Recall: 0.9901 |
| - F1: 0.3832 |
| - Accuracy: 0.7629 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - 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: linear |
| - num_epochs: 5 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.0147 | 1.0 | 2651 | 1.9499 | 0.2339 | 0.9274 | 0.3735 | 0.7659 | |
| | 0.0065 | 2.0 | 5302 | 2.4256 | 0.2371 | 0.9862 | 0.3823 | 0.7620 | |
| | 0.003 | 3.0 | 7953 | 2.6138 | 0.2390 | 0.9833 | 0.3845 | 0.7651 | |
| | 0.0013 | 4.0 | 10604 | 2.8710 | 0.2366 | 0.9869 | 0.3817 | 0.7624 | |
| | 0.0005 | 5.0 | 13255 | 2.9765 | 0.2376 | 0.9901 | 0.3832 | 0.7629 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.56.0 |
| - Pytorch 2.8.0+cu129 |
| - Datasets 4.8.2 |
| - Tokenizers 0.22.0 |
| |
