---
language:
- en
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: 40.4513375311668
---

<!-- 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: 0.3827
- Wer: 40.4513

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.6718        | 0.1129 | 500  | 0.7164          | 66.9178 |
| 0.4723        | 0.2258 | 1000 | 0.5436          | 54.4267 |
| 0.4208        | 0.3388 | 1500 | 0.4769          | 49.0925 |
| 0.3881        | 0.4517 | 2000 | 0.4404          | 45.3112 |
| 0.3739        | 0.5646 | 2500 | 0.4167          | 43.9251 |
| 0.3387        | 0.6775 | 3000 | 0.3993          | 41.2913 |
| 0.3405        | 0.7904 | 3500 | 0.3886          | 41.2099 |
| 0.3089        | 0.9033 | 4000 | 0.3827          | 40.4513 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1