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whisper-small-fa

Automatic Speech Recognition
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whisper
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metadata
library_name: transformers
language:
  - fa
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
model-index:
  - name: Whisper Small Fa - PerSTT
    results: []

Whisper Small Fa - PerSTT

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

  • eval_loss: 0.7619
  • eval_wer: 45.9459
  • eval_runtime: 2.9067
  • eval_samples_per_second: 1.032
  • eval_steps_per_second: 0.344
  • epoch: 35.0
  • step: 35

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
  • 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: 500
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0