Whisper base en - spongebob
This model is a fine-tuned version of openai/whisper-base on the Common Voice 3.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3451
- Wer: 18.3630
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: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2586 | 0.84 | 500 | 0.3588 | 19.4733 |
| 0.1667 | 1.68 | 1000 | 0.3451 | 17.4892 |
| 0.1069 | 2.53 | 1500 | 0.3451 | 18.3630 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Base model
openai/whisper-base