whisper-base
This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.9754
- Wer: 94.6341
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0739 | 100.0 | 100 | 3.9754 | 94.6341 |
Framework versions
- Transformers 4.42.4
- Pytorch 1.14.0a0+44dac51
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for stayhalley/whisper-base
Base model
openai/whisper-base