bert-tiny-privacy

This model is a fine-tuned version of prajjwal1/bert-tiny on the beki/privy dataset. It achieves the following results on the evaluation set:

• Loss: 0.0235

Model description

This model can be used to detect personal information traces from JSON, SQL, HTML and XML and can be used as a model for redacting such information.

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: 4e-05
• train_batch_size: 32
• eval_batch_size: 128
• seed: 13434865
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.01
• training_steps: 15000

Training results

Training Loss	Epoch	Step	Validation Loss
0.1891	0.19	2500	0.1369
0.0869	0.38	5000	0.0503
0.0609	0.57	7500	0.0314
0.0512	0.76	10000	0.0259
0.0493	0.95	12500	0.0240
0.048	1.14	15000	0.0237

Framework versions

• Transformers 4.36.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.0
• Tokenizers 0.15.0