Open-source wav2vec2-base-finetuned-ie model - Fine-tuned for specific speech tasks

Wav2vec2 Base Finetuned Ie

Developed by minoosh

A fine-tuned version based on facebook/wav2vec2-base model for specific tasks

Speech Recognition

Transformers

Open Source License:Apache-2.0 #Speech Recognition #High Accuracy #Multi-scenario Adaptation

Downloads 14

Release Time : 2/5/2023

Model Overview

This model is a fine-tuned version based on wav2vec2-base, primarily used for speech-related tasks. The model achieved an accuracy of 68.57% on the evaluation dataset.

Model Features

Fine-tuned based on wav2vec2-base

Optimized for specific tasks on the base model

Moderate accuracy

Achieved 68.57% accuracy on the evaluation dataset

Linear learning rate scheduling

Trained with a linear learning rate scheduling strategy

Model Capabilities

Speech processing

Speech feature extraction

Use Cases

Speech Recognition

Speech classification

Can be used for speech content classification tasks

Accuracy 68.57%

🚀 wav2vec2-base-finetuned-ie

This model is a fine - tuned version of facebook/wav2vec2-base on the None dataset. It offers improved performance in speech - related tasks, achieving specific results on the evaluation set.

🚀 Quick Start

This model is a fine - tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.9461
Accuracy: 0.6857

📚 Documentation

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 3e - 05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.1913	1.0	102	1.1911	0.4374
1.0238	2.0	204	1.0045	0.5529
0.809	3.0	306	0.9396	0.6188
0.7097	4.0	408	1.2146	0.5558
0.6082	5.0	510	1.2860	0.5752
0.4099	6.0	612	1.3618	0.5771
0.3927	7.0	714	1.1155	0.6508
0.2013	8.0	816	1.3554	0.6266
0.2208	9.0	918	1.7306	0.5674
0.1967	10.0	1020	1.6680	0.6004
0.1563	11.0	1122	1.6125	0.6402
0.0777	12.0	1224	1.7766	0.6305
0.0486	13.0	1326	1.8744	0.6324
0.0594	14.0	1428	1.9529	0.6246
0.0363	15.0	1530	1.8843	0.6334