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
- Downloads last month
- 8
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for Skier8402/whisper-small-tiny
Base model
openai/whisper-tiny