Whisper Small Odia
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 or dataset. It achieves the following results on the evaluation set:
- Loss: 0.4786
- Wer: 26.6008
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: 5e-06
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0001 | 24.01 | 250 | 0.4786 | 26.6008 |
| 0.0 | 49.01 | 500 | 0.5252 | 26.9394 |
| 0.0 | 74.01 | 750 | 0.5534 | 27.1368 |
| 0.0 | 99.01 | 1000 | 0.5644 | 26.9958 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2
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Dataset used to train arun100/whisper-small-or
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0 ortest set self-reported26.601