| --- |
| 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-gretel |
| 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-gretel |
|
|
| 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: 0.1881 |
| - Precision: 0.5606 |
| - Recall: 0.5286 |
| - F1: 0.5441 |
| - Accuracy: 0.9297 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 14 | 0.4122 | 0.1461 | 0.1857 | 0.1635 | 0.8421 | |
| | No log | 2.0 | 28 | 0.2819 | 0.472 | 0.4214 | 0.4453 | 0.8919 | |
| | No log | 3.0 | 42 | 0.2216 | 0.5546 | 0.4714 | 0.5097 | 0.9165 | |
| | No log | 4.0 | 56 | 0.1960 | 0.5814 | 0.5357 | 0.5576 | 0.9275 | |
| | No log | 5.0 | 70 | 0.1881 | 0.5606 | 0.5286 | 0.5441 | 0.9297 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.56.0 |
| - Pytorch 2.8.0+cu129 |
| - Datasets 4.8.2 |
| - Tokenizers 0.22.0 |
| |
