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Whisper Base Pashto - Augmented

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

  • Loss: 0.7901
  • Wer: 59.6482
  • Cer: 27.0947

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
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 30
  • training_steps: 600
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
1.1215 2.38 100 0.9444 68.3354 30.2694
0.8268 4.75 200 0.8267 63.2440 28.2636
0.6912 7.14 300 0.7959 62.2443 28.2123
0.5725 9.52 400 0.7896 60.5859 27.6920
0.5231 11.89 500 0.7884 59.8574 27.1273
0.4752 14.28 600 0.7901 59.6482 27.0947

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.1+cu116
  • Datasets 2.8.1.dev0
  • Tokenizers 0.13.2
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Dataset used to train ihanif/pashto-asr-base

Evaluation results