Whisper small nl last, Berb2000-GPU
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1789
- Wer: 307.7065
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: 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.151 | 0.39 | 1000 | 0.2196 | 89.8038 |
| 0.1237 | 0.78 | 2000 | 0.1978 | 46.0495 |
| 0.044 | 1.17 | 3000 | 0.1840 | 114.0796 |
| 0.0385 | 1.56 | 4000 | 0.1789 | 307.7065 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
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Dataset used to train BerB2000/whisper-small-nl-last
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0test set self-reported307.706