| --- |
| library_name: transformers |
| language: |
| - yo |
| license: apache-2.0 |
| base_model: EYEDOL/whisper-tiny-yoruba |
| tags: |
| - generated_from_trainer |
| datasets: |
| - EYEDOL/naija-voices-yoruba-split_0-1 |
| metrics: |
| - wer |
| model-index: |
| - name: EYEDOL/whisper-tiny-yoruba |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: EYEDOL/naija-voices-yoruba-split_0-1 |
| type: EYEDOL/naija-voices-yoruba-split_0-1 |
| metrics: |
| - name: Wer |
| type: wer |
| value: 0.7006286797724778 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # EYEDOL/whisper-tiny-yoruba |
|
|
| This model is a fine-tuned version of [EYEDOL/whisper-tiny-yoruba](https://huggingface.co/EYEDOL/whisper-tiny-yoruba) on the EYEDOL/naija-voices-yoruba-split_0-1 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8526 |
| - Wer Ortho: 0.7773 |
| - Wer: 0.7006 |
| |
| ## 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: 32 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - 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: constant_with_warmup |
| - lr_scheduler_warmup_steps: 0.1 |
| - num_epochs: 12 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| |
| | 1.7353 | 1.0 | 583 | 0.8680 | 0.9448 | 0.8654 | |
| | 1.6436 | 2.0 | 1166 | 0.8494 | 0.8213 | 0.7490 | |
| | 1.5173 | 3.0 | 1749 | 0.8319 | 0.8237 | 0.7470 | |
| | 1.4143 | 4.0 | 2332 | 0.8215 | 0.7845 | 0.7128 | |
| | 1.3252 | 5.0 | 2915 | 0.8135 | 0.8788 | 0.7910 | |
| | 1.2425 | 6.0 | 3498 | 0.8106 | 0.7988 | 0.7224 | |
| | 1.1664 | 7.0 | 4081 | 0.8118 | 0.8508 | 0.7635 | |
| | 1.0950 | 8.0 | 4664 | 0.8156 | 0.7628 | 0.6813 | |
| | 1.0273 | 9.0 | 5247 | 0.8191 | 0.7867 | 0.7204 | |
| | 0.9611 | 10.0 | 5830 | 0.8292 | 0.7736 | 0.6948 | |
| | 0.8975 | 11.0 | 6413 | 0.8353 | 0.8007 | 0.7126 | |
| | 0.8363 | 12.0 | 6996 | 0.8526 | 0.7773 | 0.7006 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.8.3 |
| - Tokenizers 0.22.2 |
| |
