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SPEAK-ASR/whisper-si-exp-8
This model is a fine-tuned version of openai/whisper-small on the SPEAK-ASR/openslr-sinhala-asr-preprocessed dataset. It achieves the following results on the evaluation set:
- Loss: 0.1671
- Wer: 19.7550
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 256
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 128
- total_eval_batch_size: 1024
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8759 | 1.2942 | 1500 | 0.2156 | 24.5941 |
| 0.7228 | 2.5884 | 3000 | 0.1802 | 21.0896 |
| 0.6525 | 3.8827 | 4500 | 0.1671 | 19.7550 |
Framework versions
- PEFT 0.18.1
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2
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Model tree for SPEAK-ASR/whisper-si-exp-8
Base model
openai/whisper-smallDataset used to train SPEAK-ASR/whisper-si-exp-8
Evaluation results
- Wer on SPEAK-ASR/openslr-sinhala-asr-preprocessedself-reported19.755