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tclong/
wav2vec2-base-vios

Name: wav2vec2-base-vios
Availability: InStock

automatic-speech-recognition

generated_from_trainer

vivos_dataset

apache-2.0

endpoints_compatible

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wav2vec2-base-vios

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the vivos_dataset dataset. It achieves the following results on the evaluation set:

Loss: 0.3729
Wer: 0.2427

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: 0.0003
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.4755	1.37	500	0.7991	0.5957
0.5424	2.75	1000	0.4290	0.3653
0.3586	4.12	1500	0.3809	0.2890
0.2824	5.49	2000	0.3808	0.2749
0.2249	6.87	2500	0.3467	0.2389
0.1745	8.24	3000	0.3688	0.2384
0.1459	9.61	3500	0.3729	0.2427

Framework versions

Transformers 4.11.3
Pytorch 1.10.0+cu113
Datasets 1.18.3
Tokenizers 0.10.3

tclong/wav2vec2-base-vios

wav2vec2-base-vios

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tclong/
wav2vec2-base-vios