Whisper Large-v2 Hungarian CV11

This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 hu dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3247
  • Wer: 15.5944

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: 8
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000

Training results

Training Loss Epoch Step Validation Loss Wer
0.0076 7.52 1000 0.2607 16.0332
0.0013 15.04 2000 0.2896 15.7842
0.0009 22.55 3000 0.3042 16.2378
0.0003 30.07 4000 0.3247 15.5944
0.0002 37.59 5000 0.3313 15.6004

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 mikr/whisper-large2-hu-cv11

Evaluation results