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piimasking_pytorch
shivangiss/piimasking_pytorch
piimasking_pytorch is a token classification model from shivangiss. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- May 20, 2024
- Updated
- May 21, 2024
- SHA
- 73c83a97
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Base models
Model card
From the Hugging Face model README
<!-- 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. -->
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
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- May 20, 2024
- Updated
- May 21, 2024