Whisper Base Quiztest
This model is a fine-tuned version of openai/whisper-base on the quiztest dataset. It achieves the following results on the evaluation set:
- Loss: 0.0061
- Wer: 77.6612
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: 5e-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: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2437 | 3.9683 | 500 | 0.1177 | 83.1084 |
| 0.008 | 7.9365 | 1000 | 0.0061 | 77.6612 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for tutikentuti/whisper-base-quiztest
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openai/whisper-base