| --- |
| license: apache-2.0 |
| base_model: openai/whisper-small |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: whisper-small-yoruba-07-17 |
| results: [] |
| --- |
| |
| <!-- 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-yoruba-07-17 |
|
|
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3346 |
| - Wer Ortho: 34.5068 |
| - Wer: 25.6765 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 50 |
| - num_epochs: 1 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
| |:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| |
| | 0.7951 | 0.0745 | 250 | 0.8000 | 60.4651 | 45.9597 | |
| | 0.605 | 0.1490 | 500 | 0.6408 | 50.3176 | 39.3120 | |
| | 0.5273 | 0.2235 | 750 | 0.5621 | 45.8657 | 35.7526 | |
| | 0.4483 | 0.2980 | 1000 | 0.5138 | 43.4349 | 33.8902 | |
| | 0.4158 | 0.3725 | 1250 | 0.4752 | 41.9130 | 32.5295 | |
| | 0.4032 | 0.4470 | 1500 | 0.4434 | 41.1866 | 31.6249 | |
| | 0.3261 | 0.5215 | 1750 | 0.4153 | 40.2187 | 30.3193 | |
| | 0.3606 | 0.5959 | 2000 | 0.3910 | 38.0659 | 29.1049 | |
| | 0.3008 | 0.6704 | 2250 | 0.3769 | 36.7084 | 27.5409 | |
| | 0.2938 | 0.7449 | 2500 | 0.3608 | 36.2985 | 27.0924 | |
| | 0.2933 | 0.8194 | 2750 | 0.3494 | 35.6086 | 27.0448 | |
| | 0.277 | 0.8939 | 3000 | 0.3404 | 34.5474 | 25.5682 | |
| | 0.2849 | 0.9684 | 3250 | 0.3346 | 34.5068 | 25.6765 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.42.4 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
| |
