Whisper Small Canontese X v3
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.0, the Common Voice 16.1 and the Common Voice 17.0 datasets. It achieves the following results on the evaluation set:
- Loss: 0.2650
- Wer: 55.6319
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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0845 | 0.7087 | 1000 | 0.2773 | 61.5120 |
0.0285 | 1.4174 | 2000 | 0.2697 | 56.7010 |
0.0102 | 2.1262 | 3000 | 0.2650 | 55.6319 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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Base model
openai/whisper-smallDatasets used to train PenguinbladeZ/whisper-small-hk
Evaluation results
- Wer on Common Voice 16.0self-reported55.632
- Wer on Common Voice 16.1self-reported55.632
- Wer on Common Voice 17.0self-reported55.632