whisper-tiny-en / README.md
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metadata
language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - PolyAI/minds14
metrics:
  - wer
model-index:
  - name: Whisper Tiny EN-US - Agneev M
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Minds 14
          type: PolyAI/minds14
          config: en-US
          split: train
          args: en-US
        metrics:
          - name: Wer
            type: wer
            value: 0.3488372093023256

Whisper Tiny EN-US - Agneev M

This model is a fine-tuned version of openai/whisper-tiny on the Minds 14 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6326
  • Wer Ortho: 0.3668
  • Wer: 0.3488

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: 64
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 5
  • training_steps: 50

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.3661 14.29 50 0.6326 0.3668 0.3488

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.13.3