wav2vec2-base-timit-demo-colab-test

ying-tina/wav2vec2-base-timit-demo-colab-test

wav2vec2-base-timit-demo-colab-test is a automatic speech recognition model from ying-tina. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Automatic Speech Recognition
Library: transformers
License: apache-2.0
Model type: wav2vec2
Access: Public
Created: Mar 2, 2022
Updated: Dec 5, 2021
SHA: b690d97b

Model card

From the Hugging Face model README

wav2vec2-base-timit-demo-colab-test

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: 0.4283
Wer: 0.3356

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: 0.0001
train_batch_size: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.7386	4.0	500	2.2419	1.0
0.9366	8.0	1000	0.4789	0.4807
0.3118	12.0	1500	0.4197	0.3973
0.1784	16.0	2000	0.4216	0.3614
0.1297	20.0	2500	0.4298	0.3507
0.1091	24.0	3000	0.4365	0.3437
0.0819	28.0	3500	0.4283	0.3356

Framework versions

Transformers 4.11.3
Pytorch 1.10.0+cu111
Datasets 1.13.3
Tokenizers 0.10.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Mar 2, 2022
Updated: Dec 5, 2021