README.md

metadata

language:
  - ha
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - Seon25/common_voice_16_0_
metrics:
  - wer
model-index:
  - name: Whisper Small 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: 87.20061314428051

Whisper Small Ha - Eldad Akhaumere

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

• Loss: 1.7230
• Wer Ortho: 88.6328
• Wer: 87.2006

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
• training_steps: 500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.3689	3.1847	500	1.7230	88.6328	87.2006

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1