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Vit Chess V4
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Vit Chess V4

Developed by Migga
A chess-related vision model based on Vision Transformer architecture, fine-tuned on an unknown dataset
Image Classification
Transformers
#Chess Analysis#Vision Transformer#Board Recognition
Downloads 29
Release Time : 7/21/2022

Model Overview

This model is a vision model based on the Vision Transformer architecture, specifically fine-tuned for chess-related tasks. Judging by performance metrics, it may be used for tasks such as chessboard state recognition or piece classification.

Model Features

ViT-Based Architecture
Utilizes Vision Transformer architecture, potentially better suited for processing structured visual data like chessboard images
Chess-Specialized
Specifically fine-tuned for chess-related visual tasks, likely optimized for board and piece recognition capabilities
Linear Learning Rate Scheduling
Training employs linear learning rate scheduling strategy, helping stabilize the training process

Model Capabilities

Chessboard image processing
Piece recognition
Board state analysis

Use Cases

Board Games
Board State Recognition
Identify chessboard and piece positions from images
Validation set accuracy 19.42%
Automatic Move Recording
Automatically record chess moves based on consecutive images
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