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metadata
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper Small Pashto
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs ps_af
          type: google/fleurs
          config: ps_af
          split: test
          args: ps_af
        metrics:
          - name: Wer
            type: wer
            value: 56.651029055690074

Whisper Small Pashto

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

  • Loss: 1.2273
  • Wer: 56.6510

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: 3e-07
  • 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: 800
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
2.1183 3.7 100 1.3170 76.9522
0.8565 7.41 200 0.9367 61.9930
0.2246 11.11 300 0.9642 58.8302
0.054 14.81 400 1.0876 57.9903
0.0159 18.52 500 1.1798 57.8768
0.0045 22.22 600 1.2309 56.6510
0.0026 100.0 700 1.2581 56.8478
0.0023 114.29 800 1.2710 56.7570

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2