wav2vec2-E

M-Quan/wav2vec2-E

wav2vec2-E is a automatic speech recognition model from M-Quan. 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 10, 2022
Updated: Mar 10, 2022
SHA: 00b1800c

Model card

From the Hugging Face model README

wav2vec2-E

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: 0.4832
Wer: 0.3432

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
3.5034	4.0	500	1.1620	0.8995
0.5738	8.0	1000	0.4625	0.4396
0.2142	12.0	1500	0.4791	0.3965
0.1219	16.0	2000	0.4677	0.3703
0.0854	20.0	2500	0.4782	0.3544
0.0587	24.0	3000	0.4680	0.3516
0.044	28.0	3500	0.4832	0.3432

Framework versions

Transformers 4.11.3
Pytorch 1.10.0+cu111
Datasets 1.18.4
Tokenizers 0.10.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Mar 10, 2022
Updated: Mar 10, 2022