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metadata
language:
  - it
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Italian
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          args: 'config: it, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 17.37085955328124

Whisper Small Italian

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

  • Loss: 0.2421
  • Wer: 17.3709

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
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.4521 0.1 100 1.3771 120.3480
0.7526 0.21 200 0.9120 83.8949
0.3023 0.31 300 0.4427 26.2063
0.2718 0.42 400 0.4282 25.9013
0.2823 0.52 500 0.4181 26.2757
0.3151 0.63 600 0.4095 25.0624
0.2559 0.73 700 0.4028 25.4784
0.2727 0.84 800 0.2888 19.5491
0.2532 0.94 900 0.2779 19.3832
0.232 1.05 1000 0.2722 18.6778
0.2169 1.15 1100 0.2720 18.9268
0.2493 1.26 1200 0.2741 20.0678
0.2312 1.36 1300 0.2666 18.2767
0.2158 1.47 1400 0.2651 19.6529
0.2171 1.57 1500 0.2583 18.6087
0.2074 1.68 1600 0.2551 17.6820
0.1862 1.78 1700 0.2491 17.4124
0.2044 1.89 1800 0.2475 17.8964
0.1877 1.99 1900 0.2421 17.3709

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu116
  • Datasets 2.7.1
  • Tokenizers 0.13.2