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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - PolyAI/minds14
metrics:
  - wer
model-index:
  - name: whisper-tiny-en-finetune-minds14
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: PolyAI/minds14
          type: PolyAI/minds14
          config: en-US
          split: train[450:]
          args: en-US
        metrics:
          - name: Wer
            type: wer
            value: 0.3382526564344746

whisper-tiny-en-finetune-minds14

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

  • Loss: 0.6541
  • Wer Ortho: 0.3399
  • Wer: 0.3383

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: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.3136 3.57 100 0.4883 0.3640 0.3524
0.0417 7.14 200 0.5146 0.3560 0.3442
0.0066 10.71 300 0.5736 0.3411 0.3353
0.0017 14.29 400 0.6040 0.3455 0.3418
0.0013 17.86 500 0.6226 0.3393 0.3365
0.0009 21.43 600 0.6352 0.3393 0.3365
0.0007 25.0 700 0.6436 0.3399 0.3371
0.0006 28.57 800 0.6492 0.3399 0.3383
0.0006 32.14 900 0.6530 0.3399 0.3383
0.0006 35.71 1000 0.6541 0.3399 0.3383

Framework versions

  • Transformers 4.29.2
  • Pytorch 1.13.1+cu117
  • Datasets 2.12.0
  • Tokenizers 0.13.3