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
- Downloads last month
- 26
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for arnabdhar/bert-tiny-privacy
Base model
prajjwal1/bert-tiny