| --- |
| 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: Incremental Swahili Luganda |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Mix data |
| type: mozilla-foundation/common_voice_15_0 |
| config: lg |
| split: validation |
| args: 'config: lu, split: test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 30.713561255969235 |
| --- |
| |
| <!-- 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. --> |
|
|
| # Incremental Swahili Luganda |
|
|
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Mix data dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3391 |
| - Wer: 30.7136 |
|
|
| ## 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 | |
| |:-------------:|:------:|:----:|:---------------:|:-------:| |
| | 0.1672 | 0.0998 | 500 | 0.3706 | 33.9074 | |
| | 0.172 | 0.1996 | 1000 | 0.3714 | 33.9803 | |
| | 0.2094 | 0.2995 | 1500 | 0.3640 | 33.2407 | |
| | 0.1927 | 0.3993 | 2000 | 0.3577 | 32.5233 | |
| | 0.1905 | 0.4991 | 2500 | 0.3521 | 31.8810 | |
| | 0.1735 | 0.5989 | 3000 | 0.3470 | 31.3189 | |
| | 0.157 | 0.6987 | 3500 | 0.3428 | 31.0052 | |
| | 0.1784 | 0.7986 | 4000 | 0.3391 | 30.7136 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.40.0 |
| - Pytorch 2.2.2+cu118 |
| - Datasets 2.19.0 |
| - Tokenizers 0.19.1 |
|
|
