wav2vec2-base-checkpoint-5 Open Source Speech Recognition Model - Supports Automatic Speech Recognition Tasks

Wav2vec2 Base Checkpoint 5

Developed by jiobiala24

This model is a fine-tuned speech recognition model based on wav2vec2-base-checkpoint-4 on the common_voice dataset, supporting Automatic Speech Recognition (ASR) tasks.

Speech Recognition

Transformers

Open Source License:Apache-2.0 #Speech Recognition #Low Word Error Rate #Multi-round Fine-tuning

Downloads 16

Release Time : 3/2/2022

Model Overview

A speech recognition model based on the wav2vec2 architecture, fine-tuned on the common_voice dataset for converting speech to text.

Model Features

Efficient Fine-tuning

Fine-tuned based on the pre-trained wav2vec2 model, improving recognition accuracy on the common_voice dataset.

Low Word Error Rate

Achieved a word error rate (WER) of 0.3354 on the evaluation set, demonstrating good performance.

Optimized Training

Utilized linear learning rate scheduling and the Adam optimizer for 30 training epochs to ensure model convergence.

Model Capabilities

Speech Recognition

Audio to Text Conversion

Use Cases

Speech Transcription

Speech-to-Text Service

Automatically converts speech content into text transcripts

Word error rate 0.3354

Assistive Tools

Hearing Assistance

Real-time conversion of speech to text to help hearing-impaired individuals understand spoken content

Training Loss	Epoch	Step	Validation Loss	Wer
0.3947	1.96	1000	0.5749	0.3597
0.2856	3.93	2000	0.6212	0.3479
0.221	5.89	3000	0.6280	0.3502
0.1755	7.86	4000	0.6517	0.3526
0.1452	9.82	5000	0.7115	0.3481
0.1256	11.79	6000	0.7687	0.3509
0.1117	13.75	7000	0.7785	0.3490
0.0983	15.72	8000	0.8115	0.3442
0.0877	17.68	9000	0.8290	0.3429
0.0799	19.65	10000	0.8517	0.3412
0.0733	21.61	11000	0.9370	0.3448
0.066	23.58	12000	0.9157	0.3410
0.0623	25.54	13000	0.9673	0.3377
0.0583	27.5	14000	0.9804	0.3348
0.0544	29.47	15000	0.9849	0.3354

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Wav2vec2 Base Checkpoint 5

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 wav2vec2-base-checkpoint-5

🚀 Quick Start

📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

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