This model is a fine-tuned version of Salesforce's BLIP image captioning base model on the SageMaker platform, primarily used for image caption generation tasks.

MultimodalTransformers

A sentiment analysis model based on DistilBERT, fine-tuned on sentiment datasets with an accuracy of 91.65%

Natural Language ProcessingTransformers

A sentiment classification model based on DistilBERT, fine-tuned on sentiment datasets with an accuracy of 91.5%

Natural Language ProcessingTransformers

A text sentiment classification model based on DistilBERT, fine-tuned on the emotion dataset with an accuracy of 92.9%

Natural Language ProcessingTransformers

A sentiment classification model fine-tuned on DistilBERT-base-uncased, achieving 92.8% accuracy on sentiment datasets

Natural Language ProcessingTransformers

A lightweight dialogue summarization model fine-tuned on the SAMSum dataset, trained using Amazon SageMaker and Hugging Face containers

Natural Language ProcessingTransformersEnglish

A dialogue summarization model based on BART-base architecture, trained using Amazon SageMaker and Hugging Face deep learning containers, suitable for the SAMSum dataset.

Natural Language ProcessingTransformersEnglish

A multi-class text classification model fine-tuned based on the RoBERTa-base architecture, specifically designed for emotion detection tasks, achieving 94.1% accuracy on the emotion dataset.

Natural Language ProcessingTransformersEnglish