whisper-tiny-en-US / README.md
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metadata
language:
  - en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - PolyAI/minds14
metrics:
  - wer
model-index:
  - name: Whisper tiny
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: minds14
          type: PolyAI/minds14
          config: en-US
          split: train
          args: en-US
        metrics:
          - name: Wer
            type: wer
            value: 0.3612750885478158
pipeline_tag: automatic-speech-recognition

Whisper tiny

This model is a fine-tuned version of openai/whisper-tiny on the minds14 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6491
  • Wer Ortho: 0.3572
  • Wer: 0.3613

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-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 8
  • training_steps: 45
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.0569 0.2679 15 0.6113 0.3337 0.3294
0.0364 0.5357 30 0.6443 0.3603 0.3554
0.0916 0.8036 45 0.6491 0.3572 0.3613

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1