metadata
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: []
PII-Token-Filter-Hard-gretel
This model is a fine-tuned version of 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