| | --- |
| | 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: |
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|
| | - **Loss**: 0.1628 |
| | - **Wer Ortho**: 0.1635 |
| | - **Wer**: 0.0556 |
| |
|
| | ## Training Procedure |
| |
|
| | ### Training Hyperparameters |
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|
| | 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| |
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| |
|
| | ## Framework Versions |
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|
| | - **Transformers**: 4.41.2 |
| | - **Pytorch**: 2.3.0+cu121 |
| | - **Datasets**: 2.18.0 |
| | - **Tokenizers**: 0.19.1 |
| |
|
