whisper-small-fa-7 / README.md
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metadata
language:
  - fa
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
base_model: openai/whisper-small
model-index:
  - name: Whisper Small Fa - BuzzyBuzzy
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: fa
          split: test
          args: 'config: fa, split: test'
        metrics:
          - type: wer
            value: 34.25970890624783
            name: Wer

Whisper Small Fa - BuzzyBuzzy

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: 0.6904
  • Wer: 34.2597

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: 16
  • 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: 20000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0099 0.86 2000 0.6116 37.0499
0.0079 1.72 4000 0.6340 37.3746
0.0069 2.58 6000 0.6159 35.9455
0.0015 3.44 8000 0.6187 35.3281
0.0009 4.3 10000 0.6449 35.0783
0.0007 5.15 12000 0.6440 34.8452
0.0002 6.01 14000 0.6664 34.3263
0.0001 6.87 16000 0.6817 34.3471
0.0 7.73 18000 0.6809 34.1737
0.0 8.59 20000 0.6904 34.2597

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.8.0
  • Tokenizers 0.13.2