wav2vec2-base-cv – AI Model by jiobiala24 | AlphaNeural AI

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jiobiala24/
wav2vec2-base-cv

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automatic-speech-recognition

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wav2vec2-base-cv

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

Loss: 1.1562
Wer: 0.3804

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
4.563	3.18	500	2.9826	1.0
2.0012	6.37	1000	0.9528	0.5354
0.4841	9.55	1500	0.8838	0.4325
0.2748	12.74	2000	0.9437	0.4130
0.1881	15.92	2500	0.9603	0.4005
0.1426	19.11	3000	1.0605	0.3955
0.1134	22.29	3500	1.0733	0.3897
0.0963	25.48	4000	1.1387	0.3835
0.0829	28.66	4500	1.1562	0.3804

Framework versions

Transformers 4.11.3
Pytorch 1.10.0+cu111
Datasets 1.13.3
Tokenizers 0.10.3