# BERT fine-tuning

A mental health text classification model fine-tuned based on BERT-base-uncased, which can classify text into seven mental health categories.

ruSpamNS_big is a classification model for Russian spam messages on Telegram, fine-tuned based on the DeepPavlov/distilrubert-small-cased-conversational model.

Model fine-tuned based on ModernBERT-base, achieving an F1 score of 0.3833 on the evaluation set

This model is a fine-tuned version based on bert-base-uncased, focusing on improving recall performance for specific tasks

BERT-based German text classification model for rating classification of Trustpilot user reviews.

An Italian named entity recognition model fine-tuned based on Italian-ModernBERT-base

A document Q&A specialized model fine-tuned based on sberbank-ai/ruBert-large, supporting Russian and English document Q&A tasks.

A document question-answering model fine-tuned based on sberbank-ai/ruBert-base, excelling at extracting answers from document contexts, supporting Russian and English.

This model is a fine-tuned version of ModernBERT-base on an unspecified dataset. Specific use cases and performance metrics require further details

This is a BERT model fine-tuned on the GoEmotions dataset, specifically designed for multi-label sentiment classification tasks.

This model is a BERT-Base-Uncased fine-tuned phishing site classification model that can predict whether a website belongs to the 'safe' or 'unsafe' category based on text input.

A BERT-based fine-tuned phishing email detection model that accurately identifies phishing emails versus legitimate emails.

This is a BERT model fine-tuned for spam detection with a validation accuracy of approximately 99%

A BERT model fine-tuned based on google-bert/bert-base-uncased, with unspecified specific use

medBERT-base is a BERT-based model focused on masked language modeling tasks for medical and gastroenterology texts.

BERT-based text classification model for identifying user intentions in conversations

Turkish paragraph retrieval model based on ColBERT architecture, fine-tuned on the Turkish-translated MS MARCO dataset

A fine-tuned model based on the BERT architecture, used to detect metaphorical expressions in text.

This is an Arabic reranking model based on the BERT architecture, specifically designed for Arabic text, performing reranking tasks by scoring and sorting text options.

A named entity recognition model fine-tuned based on DarkBERT, focusing on threat intelligence analysis in the field of network security.

This model is fine-tuned based on Bert-Base-Uncased and is used for the multi-label classification task of predicting protein functions based on protein amino acid sequences.

MetaHateBERT is a text classification model based on the BERT architecture, specifically designed for detecting hate speech.

BERT-based multi-label classification model for financial regulatory domains, optimized for anti-money laundering/counter-terrorism financing regulatory texts

A few-shot text classification model trained with AutoTrain, suitable for news article classification tasks

An IndoBERT-based model for identifying sexual harassment content, used to detect related content in text.

KuBERT is a Central Kurdish language model based on the BERT framework, designed to address the scarcity of Kurdish language resources and enhance computational linguistics capabilities.

A BERT-based Turkish text classification model for detecting offensive language in text

A BERT-large-uncased fine-tuned adult text classification model for identifying adult content in text.

BERT model trained on 50,000 SMILES strings for understanding and processing chemical molecular representations

A BERT-based model for detecting offensive language in Spanish, fine-tuned on a Spanish offensive language dataset.

A BERT fine-tuned SMS classification model for distinguishing spam from non-spam messages.

Fine-tuned from a pre-trained Indonesian BERT model, used for sentiment analysis of Indonesian comments and reviews, and can classify text into three categories: negative, neutral, and positive.

BERT-small based model for classifying code and natural language with over 99% accuracy

This is a Transformer model for Turkish text punctuation restoration, capable of predicting the correct positions of periods (.), commas (,), and question marks (?).

A Big Five personality prediction model fine-tuned based on BERT BASE UNCASED, which predicts five major personality traits such as extraversion and neuroticism through text analysis.

A Turkish hate speech detection model fine-tuned based on BERTurk, capable of identifying neutral, offensive, and hate speech texts.

This is a BERT model based on the Indonesian language, specifically designed for sentiment classification tasks.

A BERT model specifically designed for zero-shot text classification, achieving zero-shot learning capabilities through implicit training within a binary classification framework

This is a BERT-based zero-shot text classification model, specifically designed for zero-shot classification tasks, trained using the aspect-normalized UTCD dataset.

An Italian named entity recognition model fine-tuned based on dbmdz/bert-base-italian-cased, which performs excellently on the wiki_neural dataset.