Reactiongif-Roberta Open-source Text Classification Model - Accurately Complete Reaction GIF Classification Tasks

Reactiongif Roberta

Developed by julien-c

This model is a fine-tuned text classification model based on the distilroberta-base architecture, trained on the julien-c/reactiongif dataset, primarily used for reaction GIF classification tasks.

Text Classification

Transformers

Open Source License:Apache-2.0 #Text Classification #DistilRoBERTa Fine-tuning #Low Accuracy Model

Downloads 17

Release Time : 3/2/2022

Model Overview

This is a fine-tuned text classification model for reaction GIF classification tasks, based on the distilroberta-base architecture and trained on a specific dataset.

Model Features

Efficient and Lightweight

Based on the distilroberta-base architecture, it reduces model size while maintaining relatively high performance

Task-Specific Optimization

Specially fine-tuned for reaction GIF classification tasks

Model Capabilities

Text Classification

Sentiment Analysis

Use Cases

Social Media

Reaction GIF Classification

Classifying reaction GIFs used in social media

Accuracy 26.62%

Training Loss	Epoch	Step	Validation Loss	Accuracy
3.0528	0.44	1000	3.0265	0.2223
2.9836	0.89	2000	2.9263	0.2332
2.7409	1.33	3000	2.9041	0.2533
2.7905	1.77	4000	2.8763	0.2606
2.4359	2.22	5000	2.9072	0.2642
2.4507	2.66	6000	2.9230	0.2644

Property	Details
Model Type	Generated from trainer
Training Data	julien - c/reactiongif
Metrics	accuracy
Results	Task: Text Classification (type: text - classification), Accuracy: 0.2662102282047272

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Reactiongif Roberta

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