opp_115_first_party_collection

This model is a fine-tuned version of mukund/privbert on the OPP 115 dataset. It achieves the following results on the evaluation set:

• Loss: 0.1672
• Accuracy: 0.9491

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: 3e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	138	0.1729	0.9391
No log	2.0	276	0.1672	0.9491

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.0
• Datasets 2.1.0
• Tokenizers 0.13.3

Cite

If you use this model in research, please cite the below paper.

@article{jakarai2024,
        author  = {Md Jakaria and
                   Danny Yuxing Huang and
                   Anupam Das},
        title   = {Connecting the Dots: Tracing Data Endpoints in IoT Devices},
        journal = {Proceedings on Privacy Enhancing Technologies (PoPETs)},
        year    = {2024},
        volume  = {2024},
        number  = {3},
    }