my_pii_model

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my_pii_model

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0010

Model description

num_labels=13

id2label = { 0: 'I-STREET_ADDRESS', 1: 'I-ID_NUM', 2: 'I-NAME_STUDENT', 3: 'B-PHONE_NUM', 4: 'B-USERNAME', 5: 'B-EMAIL', 6: 'I-PHONE_NUM', 7: 'O', 8: 'B-STREET_ADDRESS', 9: 'B-URL_PERSONAL', 10: 'I-URL_PERSONAL', 11: 'B-ID_NUM', 12: 'B-NAME_STUDENT' }

label2id = { 'I-STREET_ADDRESS': 0, 'I-ID_NUM': 1, 'I-NAME_STUDENT': 2, 'B-PHONE_NUM': 3, 'B-USERNAME': 4, 'B-EMAIL': 5, 'I-PHONE_NUM': 6, 'O': 7, 'B-STREET_ADDRESS': 8, 'B-URL_PERSONAL': 9, 'I-URL_PERSONAL': 10, 'B-ID_NUM': 11, 'B-NAME_STUDENT': 12 }

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

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2