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whisper-small-en-hi
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3279
- Wer: 24.0479
Model description
Two datasets are used for two different languages, for hindi mozilla-foundation/common_voice_11_0 is used and for english google/fleurs is used. with combination of two dataset wer has decreased significantly.
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.059 | 2.52 | 1500 | 0.2881 | 24.7722 |
| 0.0084 | 5.03 | 3000 | 0.3279 | 24.0479 |
Framework versions
- Transformers 4.33.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.13.3
