cricket-project-03 Open Source Model - Outstanding Performance Based on Fine-Tuning, Evaluation Accuracy Reaches 99.87%

Cricket Project 03

Developed by rawsun00001

This model is a fine-tuned version based on microsoft/deberta-v3-base, achieving an outstanding accuracy of 99.87% on the evaluation set.

Large Language Model

Transformers

Open Source License:MIT #High-precision text classification #DeBERTa fine-tuning #Multi-metric optimization

Downloads 22

Release Time : 4/14/2025

Model Overview

A fine-tuned model based on the DeBERTa-v3-base architecture, suitable for text classification tasks. Specific use cases require additional information.

Model Features

High accuracy

Achieves 99.87% accuracy on the evaluation set, demonstrating excellent performance.

Based on DeBERTa-v3

Utilizes the advanced DeBERTa-v3-base architecture with powerful text comprehension capabilities.

Efficient training

Requires only 4 training epochs to achieve superior performance, with high training efficiency.

Model Capabilities

Text classification

Natural language understanding

Use Cases

Text analysis

Sentiment analysis

Can be used to analyze text sentiment tendencies

High-accuracy sentiment classification

Content classification

Classifies text content

99.87% classification accuracy

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.0937	1.0	1158	0.0632	0.9901	0.9873	0.9955	0.9914
0.0287	2.0	2316	0.0328	0.9957	0.9955	0.9970	0.9962
0.0113	3.0	3474	0.0158	0.9983	1.0	0.9970	0.9985
0.0095	4.0	4632	0.0108	0.9987	0.9992	0.9985	0.9989

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Cricket Project 03

Model Overview

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