Whisper Small de
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: 0.5515
- Wer Ortho: 17.4089
- Wer: 15.8852
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: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|---|---|---|---|---|---|
| 0.0015 | 16.1290 | 500 | 0.5515 | 17.4089 | 15.8852 |
Framework versions
- Transformers 4.55.0
- Pytorch 2.8.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.4
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Model tree for alphaply/whisper-small-dv
Base model
openai/whisper-smallDataset used to train alphaply/whisper-small-dv
Evaluation results
- Wer on minds14self-reported15.885
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("alphaply/whisper-small-dv", dtype="auto")