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---
library_name: transformers
---
# finetuned whisper-tiny model on custom dataset
This model is a fine-tuned version of `openai/whisper-tiny` on Serbian Mozilla/Common Voice 13. It achieves the following results on the evaluation set:
- **Loss**: 0.1628
- **Wer Ortho**: 0.1635
- **Wer**: 0.0556
## Training Procedure
### Training Hyperparameters
The following hyperparameters were used during training:
- **learning_rate**: 3e-5
- **train_batch_size**: 32
- **eval_batch_size**: 32
- **gradient_accumulation_steps**: 2
- **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**: 100
- **training_steps**: 2000
- **mixed_precision_training**: Native AMP
### Training Results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---------------|-------|------|-----------------|-----------|-------|
| 0.0600 | 1.34 | 500 | 0.1852 | 0.1800 | 0.0745|
| 0.0285 | 2.67 | 1000 | 0.1715 | 0.1710 | 0.0640|
| 0.0140 | 4.01 | 1500 | 0.1658 | 0.1685 | 0.0582|
## Framework Versions
- **Transformers**: 4.41.2
- **Pytorch**: 2.3.0+cu121
- **Datasets**: 2.18.0
- **Tokenizers**: 0.19.1
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