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  - bert
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- ## Model Card for "bert-43-multilabel-emotion-detection"
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  ### Model Description
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  This model, "bert-43-multilabel-emotion-detection", is a fine-tuned version of "bert-base-uncased", trained to classify sentences based on their emotional content into one of 43 categories in the English language. The model was trained on a combination of datasets including tweet_emotions, GoEmotions, and synthetic data, amounting to approximately 271,000 records with around 6,306 records per label.
 
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  - bert
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  - sentiment
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  - emotion
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+ - feeling
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+ - label
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  ---
 
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  ### Model Description
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  This model, "bert-43-multilabel-emotion-detection", is a fine-tuned version of "bert-base-uncased", trained to classify sentences based on their emotional content into one of 43 categories in the English language. The model was trained on a combination of datasets including tweet_emotions, GoEmotions, and synthetic data, amounting to approximately 271,000 records with around 6,306 records per label.