neunit-nihaochangchu-V3 Open-source Audio Classification Model - Precise Classification with an Accuracy of Up to 99.99%

Neunit Nihaochangchu V3

Developed by SHENMU007

An audio classification model fine-tuned based on facebook/wav2vec2-base, trained on the superb dataset with 99.99% accuracy

Audio Classification

Transformers

Open Source License:Apache-2.0 #High-precision audio classification #Fine-tuned wav2vec2 #Ultra-low loss model

Downloads 14

Release Time : 6/30/2023

Model Overview

This model is a fine-tuned model for audio classification tasks, based on the wav2vec2 architecture, demonstrating extremely high accuracy on specific datasets

Model Features

High accuracy

Achieves 99.99% accuracy on the evaluation set

Based on wav2vec2 architecture

Uses facebook/wav2vec2-base as the base model for fine-tuning

Efficient training

Optimizes the training process with mixed-precision training and gradient accumulation techniques

Model Capabilities

Audio classification

Speech feature extraction

Use Cases

Speech processing

Voice command recognition

Recognizes specific voice commands or keywords

High-accuracy command recognition

Audio content classification

Classifies and identifies audio content

Accurately distinguishes different types of audio content

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0058	1.0	3363	0.0030	0.9992
0.0078	2.0	6727	0.0038	0.9994
0.0001	3.0	10090	0.0006	0.9998
0.0001	4.0	13454	0.0006	0.9998
0.0	5.0	16815	0.0004	0.9999

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Neunit Nihaochangchu V3

Model Overview

Model Features

Model Capabilities

Use Cases

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📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

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