🌟 Buying me coffee is a direct way to show support for this project. distilbert finetuned ai4privacy v2 This model is a fine tuned version of distilbert base uncased on the English Subset of ai4privacy/pii masking 200k dataset. Useage GitHub Implementation: Ai4Privacy Model description This model has been finetuned on the World's largest open source privacy dataset. The purpose of the trained models is to remove personally identifiable information (PII) from text, especially in the context of AI assistants and LLMs. The example texts have 54 PII classes (types of sensitive data), targeting 229 discussion subjects / use cases split across business, education, psychology and legal fields, and 5 interactions styles (e.g. casual conversation, formal document, emails etc...). Take a look at the Github implementation for specific reasearch. Intended uses & limitations More information needed Training and evaluation data More information needed Training hyperparameters The following hyperparameters were used during training: learning rate: 5e 05 train batch size: 8 eval batch size: 8 seed: 42 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e 08 lr scheduler type: cosine with restarts…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy