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whisper-turbo

Automatic Speech Recognition
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metadata
library_name: transformers
language:
  - ps
license: apache-2.0
base_model: openai/whisper-large-v3-turbo
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_17_0
model-index:
  - name: Whisper Small PS - Hanif Rahman
    results: []

Whisper Small PS - Hanif Rahman

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

  • eval_loss: 0.5956
  • eval_wer_ortho: 42.8448
  • eval_wer: 42.2319
  • eval_runtime: 629.7256
  • eval_samples_per_second: 1.158
  • eval_steps_per_second: 0.073
  • epoch: 2.7211
  • step: 1200

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: 5e-06
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 200
  • training_steps: 2000
  • mixed_precision_training: Native AMP

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.20.0