whisper-medium-vi-augmented – AI Model by Scrya | AlphaNeural AI

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Scrya/
whisper-medium-vi-augmented

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automatic-speech-recognition

generated_from_trainer

mozilla-foundation/common_voice_11_0

endpoints_compatible

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Whisper Medium VI - Multi - Augmented

This model is a fine-tuned version of openai/whisper-medium on the following datasets:

It achieves the following results on the evaluation set:

Loss: 0.3696
Wer: 16.6594
Cer: 7.7625

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

Training:

mozilla-foundation/common_voice_11_0 (train+validation)
google/fleurs (train+validation)
vivos (train)

Evaluation:

mozilla-foundation/common_voice_11_0 (test)
google/fleurs (test)
vivos (test)

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 32
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.1992	1.8	1000	0.2726	17.4929	8.2562
0.0402	3.6	2000	0.3317	17.4929	8.2588
0.0073	5.4	3000	0.3429	17.6793	8.8913
0.0014	7.19	4000	0.3599	19.0283	9.5103
0.0006	8.99	5000	0.3696	16.6594	7.7625

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.7.1.dev0
Tokenizers 0.13.2