# High F1 Score

This model is a fine-tuned version based on facebook/dinov2-large, which has been optimized and trained on specific tasks.

A question-answering model fine-tuned on distilbert-base-uncased-distilled-squad, achieving an F1 score of 81.33 on the evaluation set

A QA model fine-tuned on ModernBERT, excelling on the SQuAD dataset, suitable for extractive QA tasks.

A text classification model trained with AutoTrain, suitable for few-shot learning scenarios, capable of efficiently classifying news articles.

A multilingual sentiment analysis model based on the XLM-RoBERTa architecture, specifically optimized for German, achieving an 87% F1 score in German sentiment analysis tasks.

A Thai token classification model fine-tuned based on phayathaibert, demonstrating outstanding performance on the THAI-NER dataset

A humor detection model fine-tuned based on distilbert-base-uncased, achieving an F1 score of 0.9537 on the evaluation set

A video understanding model fine-tuned on an unknown dataset based on MCG-NJU/videomae-base, achieving an F1 score of 0.7147

A sentiment classification model fine-tuned on the go_emotions dataset based on bert-base-uncased

Flair framework's built-in Persian 7-class named entity recognition model with an F1 score of 90.33 (NSURL-2019 dataset)

This model is a DistilBERT model fine-tuned on the SQuAD dataset for extractive question answering tasks, with high exact match rate and F1 score.

This model is a speech intent classification model fine-tuned from facebook/wav2vec2-base, achieving an F1 score of 0.875 on the evaluation set.

This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the FaQuAD dataset, designed for Portuguese extractive question answering tasks.

French token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base

A fine-tuned version based on the XLM-RoBERTa-base model on a specific dataset, primarily used for sequence labeling tasks, with an evaluated F1 score of 0.8561.

A multilingual named entity recognition model fine-tuned on the PANX dataset based on the xlm-roberta-base model

A fine-tuned version of the XLM-RoBERTa-base model on German and French datasets, primarily used for sequence labeling tasks.

Named Entity Recognition (NER) model fine-tuned based on the Mongolian RoBERTa-base model

German token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base

Catalan question answering model based on RoBERTa architecture, excelling in Catalan Q&A tasks

German token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base

German token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base

A token classification model fine-tuned on the PAN-X Italian dataset based on XLM-RoBERTa-base

German token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base

German token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base

A token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base, specifically designed for Italian named entity recognition tasks.

French token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base

A token classification model fine-tuned on the PAN-X German dataset based on XLM-RoBERTa-base

A German token classification model fine-tuned on the xtreme dataset based on xlm-roberta-base

A German token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base

This model is a fine-tuned version based on hfl/chinese-bert-wwm-ext on the conll2003 dataset, designed for token classification tasks.

This is a multilingual BERT model fine-tuned for English POS tagging tasks, trained on the Penn Treebank with an F1 score of 96.69.

A cross-lingual model fine-tuned on German and French datasets based on XLM-RoBERTa-base, primarily used for named entity recognition tasks.

German token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base

German token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base

A token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base, supporting Italian text processing tasks

German token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base

This model is a fine-tuned version of Seznam/small-e-czech on the WikiANN dataset for Czech named entity recognition tasks.

Italian token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base

A German token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base, designed for named entity recognition tasks.