Whisper Small Km - Kak Soky
This model is a fine-tuned version of openai/whisper-small on the SLR42 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1471
- Wer: 35.6654
Model description
The model was fine-tuned on both encoder-decoder of transformer-based.
Intended uses & limitations
The training data is limited, thus the performance is also limited to only reading speech and a limited domain (tourism).
Training and evaluation data
The training and evaluation data was split in a 9:1 ratio from Google Text-to-speech corpus.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 4
- 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3639 | 0.76 | 1000 | 0.3452 | 71.9392 |
| 0.1553 | 1.53 | 2000 | 0.2025 | 49.0494 |
| 0.0565 | 2.29 | 3000 | 0.1664 | 39.9240 |
| 0.0334 | 3.06 | 4000 | 0.1471 | 35.6654 |
Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.13.2
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