Whisper Small Hi - 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: 0.6273
- Wer: 21.3000
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: 64
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0036 | 14.01 | 1000 | 0.4864 | 21.9993 |
| 0.001 | 28.01 | 2000 | 0.5495 | 21.9592 |
| 0.0001 | 43.01 | 3000 | 0.5957 | 21.2026 |
| 0.0 | 57.01 | 4000 | 0.6168 | 21.4032 |
| 0.0 | 72.01 | 5000 | 0.6273 | 21.3000 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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