Whisper tiny en - dlantonia
This model is a fine-tuned version of openai/whisper-small on the minds14 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6625
- Wer Ortho: 22.5602
- Wer: 22.6496
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 |
|---|---|---|---|---|---|
| 0.0012 | 17.8571 | 500 | 0.6625 | 22.5602 | 22.6496 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for dlantonia/whisper-tiny-en
Base model
openai/whisper-small