# Fine-tuned BERT Model

This is a fine-tuned text classification model based on BERT-base-uncased, specifically designed to identify crime types from crime descriptions, covering 34 classification labels.

This model is a fine-tuned version of neuralmind/bert-large-portuguese-cased on the PtBrVId dataset, primarily used for Portuguese text processing tasks.

CryptoBERT is a pre-trained natural language processing model specifically designed for analyzing sentiment and language in cryptocurrency-related social media posts.

This is a Turkish news classification model trained on the interpress news dataset with an accuracy rate of 97%.

A sentiment analysis model fine-tuned based on the Turkish BERTurk model, used to determine the sentiment polarity (positive/negative) of Turkish texts