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luigisaetta/whisper-medium

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

  • Loss: 0.1531
  • Wer: 5.5543

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: 64
  • eval_batch_size: 32
  • seed: 42
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 6000

Training results

Training Loss Epoch Step Validation Loss Wer
0.2023 0.17 1000 0.1852 7.6354
0.1215 0.33 2000 0.1577 6.4088
0.0711 1.1 3000 0.1576 6.1324
0.0656 1.27 4000 0.1499 5.8786
0.0294 2.04 5000 0.1552 5.6234
0.0351 2.21 6000 0.1531 5.5543

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.8.1.dev0
  • Tokenizers 0.13.2
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Dataset used to train luigisaetta/whispermedium2plus-it

Evaluation results