Whisper Small Vi - Shiv Kumar Ganesh
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: 0.7220
- Wer: 46.6769
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
- gradient_accumulation_steps: 2
- 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: 1200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.7433 | 1.02 | 100 | 1.6824 | 155.0559 |
| 0.5929 | 2.04 | 200 | 0.8475 | 55.5824 |
| 0.1188 | 3.05 | 300 | 0.6646 | 47.2801 |
| 0.0672 | 5.0 | 400 | 0.7099 | 61.3292 |
| 0.0317 | 6.02 | 500 | 0.6951 | 49.9013 |
| 0.0169 | 7.04 | 600 | 0.7658 | 62.8866 |
| 0.0089 | 8.06 | 700 | 0.6681 | 34.2509 |
| 0.004 | 10.01 | 800 | 0.6875 | 43.8364 |
| 0.0015 | 11.03 | 900 | 0.7129 | 46.8195 |
| 0.0011 | 12.04 | 1000 | 0.7194 | 47.4775 |
| 0.0011 | 13.06 | 1100 | 0.7217 | 46.1505 |
| 0.001 | 15.01 | 1200 | 0.7220 | 46.6769 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2
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