metadata
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: piimasking_pytorch
results: []
piimasking_pytorch
This model is a fine-tuned version of distilbert/distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0654
- Precision: 0.9137
- Recall: 0.9428
- F1: 0.9280
- Accuracy: 0.9751
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0854 | 1.0 | 10463 | 0.0744 | 0.9116 | 0.9312 | 0.9213 | 0.9700 |
| 0.064 | 2.0 | 20926 | 0.0629 | 0.9109 | 0.9387 | 0.9246 | 0.9749 |
| 0.0483 | 3.0 | 31389 | 0.0654 | 0.9137 | 0.9428 | 0.9280 | 0.9751 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1