whisper-tiny-ha / README.md
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metadata
language:
  - ha
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - Seon25/common_voice_16_0_
metrics:
  - wer
model-index:
  - name: Whisper Tiny Ha - Eldad Akhaumere
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 16.0
          type: Seon25/common_voice_16_0_
          config: ha
          split: None
          args: 'config: ha, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 107.2810883310979

Whisper Tiny Ha - Eldad Akhaumere

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 2.5851
  • Wer Ortho: 108.4180
  • Wer: 107.2811

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 15.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
1.3176 3.1847 500 2.1073 133.8086 132.4392
0.624 6.3694 1000 2.2333 110.4492 111.1324
0.2135 9.5541 1500 2.4375 101.6211 100.4407
0.0593 12.7389 2000 2.5851 108.4180 107.2811

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1