whisper-large-v3-ft-fz-cv-cy

This model is a fine-tuned version of openai/whisper-large-v3 on the DewiBrynJones/commonvoice_18_0_cy default dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5067
  • Wer: 0.2715

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: 16
  • 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
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1024 4.0161 1000 0.3592 0.2914
0.0052 8.0321 2000 0.4336 0.2667
0.0014 12.0482 3000 0.4721 0.2708
0.0006 16.0643 4000 0.4972 0.2700
0.0005 20.0803 5000 0.5067 0.2715

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.4.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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Dataset used to train DewiBrynJones/whisper-large-v3-ft-fz-cv-cy

Evaluation results

  • Wer on DewiBrynJones/commonvoice_18_0_cy default
    self-reported
    0.272