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whisper_finetune

Automatic Speech Recognition
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whisper
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metadata
language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
model-index:
  - name: Whisper Tiny En - Abhishek Singh
    results: []

Whisper Tiny En - Abhishek Singh

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:

  • eval_loss: 0.5896
  • eval_wil: 42.8626
  • eval_runtime: 1949.885
  • eval_samples_per_second: 5.129
  • eval_steps_per_second: 0.641
  • epoch: 0.05
  • step: 24000

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 500000
  • mixed_precision_training: Native AMP

Framework versions

  • Transformers 4.29.0.dev0
  • Pytorch 2.0.0+cu118
  • Datasets 2.11.0
  • Tokenizers 0.13.3