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Whisper Base Vi - DuyTa

This model is a fine-tuned version of openai/whisper-base on the Vivos dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2565
  • Wer: 25.0583

Model description

Finetune Whisper model on Vietnamese Dataset

Intended uses & limitations

More information needed

Training and evaluation data

Vivos

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 4000

Training results

Training Loss Epoch Step Validation Loss Wer
0.2096 1.37 1000 0.2949 32.0383
0.1205 2.74 2000 0.2548 26.8583
0.0767 4.12 3000 0.2549 25.3432
0.0532 5.49 4000 0.2565 25.0583

Framework versions

  • Transformers 4.31.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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Finetuned from

Dataset used to train DuyTa/vi_whisper

Evaluation results