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FT-10m

Automatic Speech Recognition
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metadata
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_6_1
metrics:
  - wer
model-index:
  - name: Whisper Small Frisian 10m
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 6.1
          type: mozilla-foundation/common_voice_6_1
          args: 'config: frisian, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 72.75540681564648

Whisper Small Frisian 10m

This model is a fine-tuned version of openai/whisper-small on the Common Voice 6.1 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6189
  • Wer: 72.7554

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-06
  • 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: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
2.2806 25.0 200 2.4315 86.9013
0.5256 50.0 400 1.6206 77.5451
0.0145 75.0 600 1.5883 73.7378
0.0055 100.0 800 1.6120 72.8274
0.0044 125.0 1000 1.6189 72.7554

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.2.2+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1