bsc_ai_thesis_torgo_model-1 Open-source Speech Processing Model - Fine-tuning Optimization Results in Good Performance on Evaluation Sets

Bsc Ai Thesis Torgo Model 1

Developed by Juardo

A speech processing model fine-tuned based on facebook/wav2vec2-base, demonstrating excellent performance on the evaluation set

Speech Recognition

Transformers

Open Source License:Apache-2.0 #Speech Recognition #High Accuracy #Low Loss Value

Downloads 19

Release Time : 6/30/2023

Model Overview

This model is a fine-tuned version based on the wav2vec2-base architecture, primarily used for speech-related tasks, achieving high accuracy and F1 scores on the evaluation set.

Model Features

High Accuracy

Achieves 86.25% accuracy on the evaluation set

Balanced Performance

Balanced performance with 83.49% precision and 90.55% recall, achieving an F1 score of 86.87%

Fine-tuned wav2vec2

Optimized based on the mature wav2vec2-base architecture

Model Capabilities

Speech Processing

Speech Feature Extraction

Use Cases

Speech Recognition

Speech Classification

Can be used for speech content classification tasks

Accuracy 86.25%

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.6855	0.96	12	0.6603	0.6225	0.5772	0.9303	0.7124
0.5875	2.0	25	0.5249	0.785	0.7533	0.8507	0.7991
0.4858	2.96	37	0.5584	0.7575	0.6940	0.9254	0.7932
0.3951	4.0	50	0.5366	0.785	0.7220	0.9303	0.8130
0.3962	4.96	62	0.4707	0.805	0.7450	0.9303	0.8274
0.3069	6.0	75	0.4032	0.8325	0.8190	0.8557	0.8370
0.2973	6.96	87	0.3753	0.855	0.8593	0.8507	0.855
0.2585	8.0	100	0.3719	0.8625	0.8259	0.9204	0.8706
0.2365	8.96	112	0.3503	0.855	0.8357	0.8856	0.8599
0.2244	9.6	120	0.3532	0.8625	0.8349	0.9055	0.8687

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Bsc Ai Thesis Torgo Model 1

Model Overview

Model Features

Model Capabilities

Use Cases

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Model description

Intended uses & limitations

Training and evaluation data

Training procedure

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