Whisper Small Hi - Pradyum Agarwal
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7131
- Wer: 14.9062
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: 10
- 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: 40
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8322 | 0.25 | 5 | 0.8398 | 18.9812 |
| 0.8922 | 0.5 | 10 | 0.8395 | 18.9812 |
| 0.8043 | 0.75 | 15 | 0.8365 | 18.1769 |
| 0.7984 | 1.0 | 20 | 0.8277 | 18.2306 |
| 0.7597 | 1.25 | 25 | 0.8099 | 17.4263 |
| 0.8054 | 1.5 | 30 | 0.7848 | 16.9973 |
| 0.7904 | 1.75 | 35 | 0.7500 | 15.9786 |
| 0.762 | 2.0 | 40 | 0.7131 | 14.9062 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small