| --- |
| language: |
| - sw |
| license: apache-2.0 |
| base_model: openai/whisper-small |
| tags: |
| - generated_from_trainer |
| datasets: |
| - mozilla-foundation/common_voice_15_0 |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Small Luganda |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 15.0 |
| type: mozilla-foundation/common_voice_15_0 |
| config: lg |
| split: validation |
| args: 'config: lu, split: test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 42.958416092634074 |
| --- |
| |
| <!-- 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. --> |
|
|
| # Whisper Small Luganda |
|
|
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 15.0 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4483 |
| - Wer: 42.9584 |
|
|
| ## 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: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 16 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - training_steps: 4000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:------:|:----:|:---------------:|:-------:| |
| | 0.8089 | 0.0682 | 500 | 0.8624 | 73.2282 | |
| | 0.6106 | 0.1364 | 1000 | 0.6437 | 59.8234 | |
| | 0.539 | 0.2045 | 1500 | 0.5589 | 51.8256 | |
| | 0.462 | 0.2727 | 2000 | 0.5167 | 48.5304 | |
| | 0.4342 | 0.3409 | 2500 | 0.4888 | 46.1205 | |
| | 0.4226 | 0.4091 | 3000 | 0.4673 | 44.8168 | |
| | 0.3951 | 0.4772 | 3500 | 0.4545 | 43.7128 | |
| | 0.4014 | 0.5454 | 4000 | 0.4483 | 42.9584 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.40.0 |
| - Pytorch 2.2.2+cu118 |
| - Datasets 2.19.0 |
| - Tokenizers 0.19.1 |
|
|
