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Whisper largeV2 dutch MLS

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

  • Loss: 0.2031
  • Wer: 10.5916

Model description

The model is fine-tuned for 4000 updates/steps on multilingual librispeech Dutch train data.

  • Zero-shot - 9.3 (MLS Dutch test)
  • Fine-tune MLS Dutch train - 10.59 (MLS Dutch test)

Even after fine-tuning the model is doing worse than the zero-shot model.

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: 4
  • 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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2515 0.25 1000 0.2579 12.9776
0.24 0.5 2000 0.2361 11.2418
0.1308 0.75 3000 0.2335 10.7503
0.1072 1.0 4000 0.2031 10.5916

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 sgangireddy/whisper-largev2-mls-dutch

Space using sgangireddy/whisper-largev2-mls-dutch 1

Evaluation results