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FT-Frisian-10m_new

Automatic Speech Recognition
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whisper
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FT-Frisian-10m_new / README.md
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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: 56.253787203707006

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: 1.4198
  • Wer: 56.2538

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
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 250
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.6208 3.3333 50 1.6201 70.3083
0.0687 6.6667 100 1.4034 58.9699
0.0038 10.0 150 1.3975 56.5104
0.0019 13.3333 200 1.4150 56.2966
0.0015 16.6667 250 1.4198 56.2538

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1