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metadata
language:
  - ar
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - Martha-987/MyOwnData
metrics:
  - wer
model-index:
  - name: Whisper Small Ar- Martha
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: MyOwnData
          type: Martha-987/MyOwnData
          config: default
          split: test
          args: 'config: ar, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 47.48124330117899

Whisper Small Ar- Martha

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

  • Loss: 0.4467
  • Wer: 47.4812

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: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.276 2.54 1000 0.4467 47.4812

Framework versions

  • Transformers 4.27.0.dev0
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2