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whisper-small-vi – AI Model by nhannguyen101193 | AlphaNeural AI

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nhannguyen101193/
whisper-small-vi

like

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automatic-speech-recognition

generated_from_trainer

mozilla-foundation/common_voice_11_0

openai/whisper-small

endpoints_compatible

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Whisper Small vi - Nhan

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

eval_loss: 0.6825
eval_wer: 30.6373
eval_runtime: 467.4643
eval_samples_per_second: 2.725
eval_steps_per_second: 0.342
epoch: 6.9444
step: 1000

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: 1e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 4000
mixed_precision_training: Native AMP

Framework versions

Transformers 4.48.3
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0