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update model card README.md
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metadata
language:
  - pt
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Portuguese
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 pt
          type: mozilla-foundation/common_voice_11_0
          config: pt
          split: test
          args: pt
        metrics:
          - name: Wer
            type: wer
            value: 14.884437596302003

Whisper Small Portuguese

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

  • Loss: 0.3191
  • Wer: 14.8844
  • Cer: 5.7447

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-06
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
2.9379 0.92 500 0.4783 17.3806 7.0572
2.1727 1.84 1000 0.3721 17.2727 6.7975
1.7856 2.76 1500 0.3466 16.3790 6.4023
1.7803 3.68 2000 0.3372 15.9014 6.2089
1.8312 4.6 2500 0.3303 15.7473 6.0901
1.6403 5.52 3000 0.3256 15.9476 6.1896
1.536 6.45 3500 0.3235 15.5008 6.0928
1.4223 7.37 4000 0.3209 15.3621 6.0735
1.4652 8.29 4500 0.3209 15.2696 5.9326
1.2572 9.21 5000 0.3191 14.8844 5.7447
1.7142 10.13 5500 0.3182 15.0077 5.8469
1.4195 11.05 6000 0.3171 15.0693 5.8856
1.3965 11.97 6500 0.3167 15.0539 5.8580

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.12.1+cu116
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2