wav2vec2-vivos – AI Model by An24 | AlphaNeural AI

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An24/
wav2vec2-vivos

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facebook/wav2vec2-base

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wav2vec2-vivos

This model is a fine-tuned version of facebook/wav2vec2-base on the vivos dataset. It achieves the following results on the evaluation set:

Loss: 0.3014
Wer: 0.1730

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: 0.0002
train_batch_size: 32
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.3
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
6.9735	2.0	146	3.8105	1.0
3.4566	4.0	292	3.5691	1.0
3.0957	6.0	438	1.5923	0.9375
0.7156	8.0	584	0.4616	0.3431
0.3195	10.0	730	0.3547	0.2452
0.2113	12.0	876	0.3117	0.2053
0.163	14.0	1022	0.3106	0.1868
0.1486	16.0	1168	0.3037	0.1748
0.1047	18.0	1314	0.3008	0.1728
0.0963	20.0	1460	0.3014	0.1730

Framework versions

Transformers 4.44.0
Pytorch 2.4.0
Datasets 2.21.0
Tokenizers 0.19.1