Whisper Medium Thai - Parinthapat Pengpun

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

  • eval_loss: 0.1875
  • eval_wer: 17.5807
  • eval_cer: 8.9942
  • eval_runtime: 14734.8594
  • eval_samples_per_second: 0.742
  • eval_steps_per_second: 0.046
  • epoch: 10.02
  • step: 11000

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: 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: 15000
  • mixed_precision_training: Native AMP

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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Datasets used to train parinzee/whisper-medium-th-cv11-fleurs