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whisper-it-small-augmented

Automatic Speech Recognition
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PyTorch
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Italian
whisper
whisper-event
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metadata
language:
  - it
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Italian - Robust
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 it
          type: mozilla-foundation/common_voice_11_0
          config: it
          split: test
          args: it
        metrics:
          - name: WER
            type: wer
            value: 8

Whisper Small Italian - Robust

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

  • Loss: 0.1980
  • Wer: 8.7457

IMPORTANT The model has been trained using data augmentation to improve its generalization capabilities and robustness. The results on the eval set during training are biased towards data augmentation applied to evaluation data.

Results on eval set

  • Mozilla CV 11.0 - Italian: 8.00 wer (using official script)
  • TODO

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: 5e-05
  • train_batch_size: 64
  • eval_batch_size: 32
  • 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: 25000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1927 1.0 2500 0.2506 14.9991
0.0736 2.01 5000 0.2258 12.7864
0.0413 3.01 7500 0.2144 11.4508
0.0201 4.02 10000 0.2146 10.8774
0.0129 5.02 12500 0.2127 10.6920
0.0091 6.03 15000 0.2117 10.2867
0.0043 7.03 17500 0.2076 9.6860
0.0018 8.04 20000 0.2065 9.4235
0.0013 9.04 22500 0.2003 8.9105
0.0009 10.05 25000 0.1978 8.7497

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1
  • Tokenizers 0.13.2