# Linear Learning Rate Scheduling

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

A text summarization generation model fine-tuned based on t5-small, performing well in the field of financial news

A speech recognition model fine-tuned from facebook/hubert-large-ls960-ft, trained on the LibriSpeech dataset

Large German text processing model based on the BART architecture, suitable for various natural language processing tasks

A biomedical named entity recognition model fine-tuned based on microsoft/biogpt

Text-to-speech model fine-tuned based on microsoft/speecht5_tts

A language model fine-tuned on an unknown dataset, trained using the Transformers library

A text classification model fine-tuned based on distilbert-base-uncased, trained for specific tasks.

A text-to-speech model fine-tuned on the VoxPopuli dataset based on microsoft/speecht5_tts

Model fine-tuned based on bert-base-multilingual-cased, achieving 99.93% accuracy on the evaluation set

An audio classification model fine-tuned based on openai/whisper-tiny, achieving 87% accuracy on the evaluation set

A reward model fine-tuned based on Qwen/Qwen2-0.5B-Instruct, used to evaluate and optimize the quality of generated content

Image orientation correction model based on SwinV2 architecture for automatic detection and correction of image orientation

This model is a fine-tuned text summarization model based on facebook/bart-large-cnn, excelling in generating summaries for legal texts.

Emotion dominance analysis model fine-tuned based on RobBERT-v2 Dutch foundation model

This model is a fine-tuned version of the RobBERT v2 Dutch base model for sentiment analysis tasks, primarily used for sentiment classification of Dutch texts.

This model is a fine-tuned speech recognition model based on openai/whisper-large-v2, achieving a word error rate of 4.6858 on a specific domain dataset.

A fine-tuned speech processing model based on wav2vec2-base-finetuned, achieving 98.82% accuracy on the evaluation set

This model is a table structure recognition model, likely used to extract structural information of tables from documents.

A fine-tuned speech synthesis model based on microsoft/speecht5_tts, trained on an unknown dataset with a validation loss of 0.3771.

A speech emotion analysis model fine-tuned based on facebook/wav2vec2-base, achieving 70.87% accuracy on the evaluation set

Object detection model based on DETR architecture, using ResNet50 as the backbone network, fine-tuned on a specific dataset

A text summarization generation model fine-tuned based on Falconsai/text_summarization, supporting the extraction of key information from long texts to generate concise summaries.

GPT-2 fine-tuned text generation model on the SST dataset

This model is a summary generation model trained from scratch on an unknown dataset, primarily used for biomedical text processing tasks.

A document understanding model fine-tuned from Yazawa/donut-base-sroie, suitable for structured document information extraction tasks

This model is a fine-tuned version of google/pegasus-cnn_dailymail on the samsum dataset, primarily used for text summarization tasks.

An audio classification model fine-tuned based on facebook/wav2vec2-base, achieving 58.92% accuracy on the evaluation set

A model fine-tuned based on facebook/detr-resnet-50 for object detection tasks

Fine-tuned image-to-text model based on microsoft/git-base

This model is a fine-tuned version of distilhubert on the GTZAN music classification dataset, primarily used for music genre classification tasks.

Model fine-tuned on custom datasets based on Linly-Chinese-LLaMA-7b-hf

A Korean-English translation model fine-tuned based on Helsinki-NLP's opus-mt-ko-en model

A model for gender classification based on text or image data, with unspecified training data.

Model fine-tuned based on Bennet1996/donut-base-sroie8, specific uses and functionalities require more information

HingFlow is a Transformer-based English-Hindi translation model trained on the IITB English-Hindi dataset, achieving high BLEU scores.

A speech processing model fine-tuned based on facebook/wav2vec2-large, supporting speech recognition tasks

This model is a fine-tuned audio classification model based on MIT/ast-finetuned-audioset-10-10-0.4593, achieving 60.76% accuracy on the evaluation set.

This model is a fine-tuned version of minoosh/wav2vec2-base-finetuned-ie on the shEMO dataset, primarily used for speech emotion recognition tasks.

OCR model trained on image folder datasets for text recognition in PDF documents