Whisper tiny Canadian accent
This model is a fine-tuned version of openai/whisper-tiny on the Canadian English dataset. It achieves the following results on the evaluation set:
- Loss: 0.4251
- Wer: 20.8760
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: 2
- eval_batch_size: 1
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3021 | 1.0 | 1000 | 0.4220 | 21.3218 |
| 0.1128 | 2.0 | 2000 | 0.4251 | 20.8760 |
Framework versions
- Transformers 5.23.0.dev0
- Pytorch 2.11.0+cu130
- Datasets 5.1.0
- Tokenizers 0.23.3
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Model tree for Quiglee2/whisper-tiny-canadian-ft
Base model
openai/whisper-tinyDataset used to train Quiglee2/whisper-tiny-canadian-ft
Evaluation results
- Wer on Canadian Englishself-reported20.876