Whisper Small Assamese - Drishti Sharma
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: 0.5164
- Wer: 30.6502
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: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 150
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.1539 | 3.02 | 50 | 0.7835 | 89.0863 |
| 0.2089 | 7.0 | 100 | 0.3041 | 37.7378 |
| 0.0428 | 10.02 | 150 | 0.3760 | 33.9118 |
| 0.0141 | 14.01 | 200 | 0.4400 | 31.6538 |
| 0.0059 | 17.02 | 250 | 0.4472 | 31.2774 |
| 0.0022 | 21.01 | 300 | 0.4696 | 31.0475 |
| 0.0005 | 24.03 | 350 | 0.5032 | 31.2983 |
| 0.0003 | 28.02 | 400 | 0.5051 | 30.7129 |
| 0.0003 | 32.0 | 450 | 0.5137 | 30.7338 |
| 0.0003 | 35.02 | 500 | 0.5164 | 30.6502 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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