| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: openai/whisper-small |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: whisper-small-akan |
| 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-akan |
|
|
| 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: 0.9537 |
| - Wer: 35.7102 |
|
|
| ## 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: 0.0001 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - training_steps: 2000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | 0.0761 | 10.0 | 250 | 0.6787 | 41.9921 | |
| | 0.0557 | 20.0 | 500 | 0.7485 | 42.4731 | |
| | 0.0273 | 30.0 | 750 | 0.8616 | 40.3509 | |
| | 0.0123 | 40.0 | 1000 | 0.9085 | 38.3701 | |
| | 0.0024 | 50.0 | 1250 | 0.9378 | 36.7572 | |
| | 0.0002 | 60.0 | 1500 | 0.9400 | 36.5025 | |
| | 0.0001 | 70.0 | 1750 | 0.9507 | 35.9366 | |
| | 0.0001 | 80.0 | 2000 | 0.9537 | 35.7102 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.44.2 |
| - Pytorch 2.4.0+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
| |
