razhan / whisper-small-me

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Model's Last Updated: February 12 2025
automatic-speech-recognition

Introduction of whisper-small-me

Model Details of whisper-small-me

whisper-small-me

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4509
  • Mazanderani Wer: 0.5278
  • Mazanderani Cer: 0.1615
  • Gilaki Wer: 0.9176
  • Gilaki Cer: 0.3175
  • Zazaki Wer: 0.6324
  • Zazaki Cer: 0.2020
  • Laki Kurdish Wer: 0.4904
  • Laki Kurdish Cer: 0.1247
  • Talysh Wer: 1.0
  • Talysh Cer: 0.5
  • Hawrami Wer: 0.3459
  • Hawrami Cer: 0.0708
  • Southern Kurdish Wer: 0.4930
  • Southern Kurdish Cer: 0.1718
  • Avg Wer: 0.6296
  • Avg Cer: 0.2212
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: 128
  • eval_batch_size: 128
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • total_train_batch_size: 256
  • total_eval_batch_size: 256
  • optimizer: Use 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: 100
  • num_epochs: 5.0
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Mazanderani Wer Mazanderani Cer Gilaki Wer Gilaki Cer Zazaki Wer Zazaki Cer Laki Kurdish Wer Laki Kurdish Cer Talysh Wer Talysh Cer Hawrami Wer Hawrami Cer Southern Kurdish Wer Southern Kurdish Cer Avg Wer Avg Cer
0.6946 1.0 82 0.7662 0.8120 0.3224 0.9556 0.3751 1.0270 1.0389 0.7939 0.2733 0.9167 0.3333 0.5246 0.1155 0.6801 0.2192 0.8157 0.3825
0.3864 2.0 164 0.5172 0.6093 0.1846 0.9579 0.3454 0.7451 0.2813 0.5644 0.1547 1.0 0.5 0.3806 0.0773 0.5484 0.1743 0.6865 0.2454
0.3234 3.0 246 0.4686 0.5476 0.1652 0.9633 0.3514 0.6740 0.2363 0.5231 0.1362 1.0 0.5 0.3533 0.0722 0.4936 0.1674 0.6507 0.2327
0.2786 4.0 328 0.4527 0.5278 0.1596 0.9083 0.3179 0.6422 0.2133 0.5047 0.1334 1.0 0.5 0.3485 0.0732 0.4948 0.1769 0.6323 0.2249
0.2586 5.0 410 0.4509 0.5278 0.1615 0.9176 0.3175 0.6324 0.2020 0.4904 0.1247 1.0 0.5 0.3459 0.0708 0.4930 0.1718 0.6296 0.2212
Framework versions
  • Transformers 4.49.0.dev0
  • Pytorch 2.6.0+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0

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