# Mini-batch training

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 of Alt4nsuh/long_promt-finetuned-first, suitable for handling long text prompt tasks.

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

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

This model is a fine-tuned version based on /gemini/data-1/sikuroberta_vocabtxt. Specific uses and functionalities require further information.

A speech processing model fine-tuned based on microsoft/wavlm-large, achieving an accuracy of 73.33% on the evaluation set

A multi-label classification model fine-tuned from google/vit-base-patch16-224-in21k with an accuracy of 73.7%

Speech processing model based on the wav2vec2 architecture, training details not fully disclosed

RoBERTa model fine-tuned on culinary-related datasets based on bert-base-uncased, suitable for NLP tasks such as text classification

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base, utilizing data augmentation techniques (augmentation ratio of 0.1).

A summarization generation model fine-tuned based on Ameer05/tokenizer-repo, performing well on ROUGE metrics

This is a Bengali speech recognition model fine-tuned on a specific dataset, primarily used for speech-to-text tasks.

Pre-trained language model based on Transformer architecture, suitable for various NLP tasks

A fine-tuned model based on bert-base-multilingual-uncased, specific purpose not clearly stated

Text generation model fine-tuned based on GPT-2