openai/whisper-large-v2-welsh

This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2947
  • Wer: 18.0609

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: 4
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 8
  • 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: 50
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss Wer
0.4438 0.2 100 0.4208 27.3594
0.3255 0.4 200 0.3633 23.6118
0.2856 0.6 300 0.3248 20.7023
0.1811 1.14 400 0.3011 18.5534
0.1404 1.34 500 0.2947 18.0609

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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Dataset used to train kpriyanshu256/whisper-large-v2-cy-500-32-1e-05

Evaluation results