Whisper Small Assamese
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5698
- Wer: 66.7815
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
- 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 |
|---|---|---|---|---|
| 0.2471 | 2.7027 | 200 | 0.3792 | 74.9368 |
| 0.0533 | 5.4054 | 400 | 0.3930 | 68.5275 |
| 0.0128 | 8.1081 | 600 | 0.4844 | 67.5396 |
| 0.0022 | 10.8108 | 800 | 0.5584 | 67.0342 |
| 0.0006 | 13.5135 | 1000 | 0.5698 | 66.7815 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small