whisper-base-ps / README.md
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metadata
library_name: transformers
language:
  - ps
license: apache-2.0
base_model: openai/whisper-base
tags:
  - generated_from_trainer
datasets:
  - SherwinDesouza/pashto-common-voice-20
metrics:
  - wer
model-index:
  - name: Whisper Base Ps - ZFA
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 20.0
          type: SherwinDesouza/pashto-common-voice-20
          args: 'config: ps, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 54.07066052227343

Whisper Base Ps - ZFA

This model is a fine-tuned version of openai/whisper-base on the Common Voice 20.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6856
  • Wer: 54.0707

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • 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
0.2602 5.9199 1000 0.6856 54.0707

Framework versions

  • Transformers 4.53.2
  • Pytorch 2.7.1+cu126
  • Datasets 4.0.0
  • Tokenizers 0.21.2