Whisper_small_Khmer
This model is a fine-tuned version of openai/whisper-small on the google/fleurs km_kh dataset. It achieves the following results on the evaluation set:
- Loss: 1.9221
- Wer: 84.9417
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: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5571 | 40.0 | 400 | 1.2022 | 89.9564 |
| 0.0088 | 80.0 | 800 | 1.7980 | 86.6669 |
| 0.0023 | 120.0 | 1200 | 1.9221 | 84.9417 |
| 0.0002 | 160.0 | 1600 | 2.0559 | 85.4326 |
| 0.0002 | 200.0 | 2000 | 2.0787 | 85.6536 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
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Dataset used to train steja/whisper-small-khmer
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Evaluation results
- Wer on google/fleurs km_khtest set self-reported84.942