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metadata
language:
  - fa
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper small Persian
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 fa
          type: mozilla-foundation/common_voice_11_0
          config: fa
          split: test
        metrics:
          - name: Wer
            type: wer
            value: 32.8995086472
pipeline_tag: automatic-speech-recognition

Whisper small Persian

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

  • Loss: 0.4924
  • Wer: 32.8995

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-06
  • train_batch_size: 8
  • eval_batch_size: 16
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • total_eval_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.5533 1.56 500 0.7044 54.5499
0.3951 3.12 1000 0.5893 47.5210
0.3296 4.67 1500 0.5429 42.6451
0.2662 6.23 2000 0.5223 40.6644
0.2535 7.79 2500 0.5045 38.5304
0.224 9.35 3000 0.5002 36.8822
0.2204 10.9 3500 0.4967 35.3076
0.2024 12.46 4000 0.4951 34.9883
0.2099 14.02 4500 0.4921 34.9842
0.1836 15.58 5000 0.4924 34.8995

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1
  • Tokenizers 0.13.2