README.md

metadata

license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper Small English
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs en_us
          type: google/fleurs
          config: en_us
          split: test
          args: en_us
        metrics:
          - name: Wer
            type: wer
            value: 7.990755655157924

Whisper Small English

This model is a fine-tuned version of openai/whisper-small.en on the google/fleurs en_us dataset. It achieves the following results on the evaluation set:

• Loss: 0.6007
• Wer: 7.9908

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: 32
• 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: 5000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0005	24.0	1000	0.5092	7.5566
0.0002	48.01	2000	0.5528	7.7526
0.0001	73.0	3000	0.5785	7.8507
0.0001	97.0	4000	0.5936	7.9908
0.0001	121.01	5000	0.6007	7.9908

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.0+cu117
• Datasets 2.7.1.dev0
• Tokenizers 0.13.2