Whisper Tiny Sw - Skier8402
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 13 dataset using the swahili only.
Model description
More information needed.
Intended uses & limitations
The model was trained without enough noise added as a form of data augmentation. Do not use this production. I recommend using a larger version of whisper with more hyperparameter tuning especially the learning rate, momentum, weight decay and adjusting the batch size.
Training and evaluation data
I followed the tutorial here. Very minimum edits to the code were done following this tutorial.
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
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
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