Whisper small nl last, Berb2000-GPU

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

  • Loss: 0.1789
  • Wer: 307.7065

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: 8
  • 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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.151 0.39 1000 0.2196 89.8038
0.1237 0.78 2000 0.1978 46.0495
0.044 1.17 3000 0.1840 114.0796
0.0385 1.56 4000 0.1789 307.7065

Framework versions

  • Transformers 4.27.0.dev0
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2
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Dataset used to train BerB2000/whisper-small-nl-last

Evaluation results