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Wav2vec2 Base Finetuned Ks
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Wav2vec2 Base Finetuned Ks

Developed by motheecreator
An audio classification model fine-tuned on an audio folder dataset based on the wav2vec2-base model, achieving 99.82% accuracy on the validation set
Audio Classification
Transformers
Open Source License:Apache-2.0#Audio Classification#High Accuracy#Speech Recognition
Downloads 54
Release Time : 4/16/2024

Model Overview

This model is a fine-tuned version of the wav2vec2-base architecture, specifically designed for audio classification tasks. It demonstrates extremely high accuracy (99.82%) on the evaluation set, making it suitable for applications requiring high-precision audio classification.

Model Features

High Accuracy
Achieves 99.82% classification accuracy on the validation set
Based on wav2vec2 Architecture
Utilizes the proven wav2vec2-base architecture as the foundation model
Efficient Fine-tuning
Requires only 5 training epochs to achieve high performance

Model Capabilities

Audio Classification
Speech Feature Extraction

Use Cases

Speech Recognition
Keyword Spotting
Identify specific keywords or phrases in audio
High-accuracy keyword detection
Audio Analysis
Audio Event Detection
Detect and classify specific events or sounds in audio
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