---
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: 31.718294383636902
---

<!-- 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: 0.3430
- Wer: 31.7183

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2355        | 0.0894 | 500  | 0.3831          | 35.9432 |
| 0.2275        | 0.1789 | 1000 | 0.3818          | 35.3379 |
| 0.245         | 0.2683 | 1500 | 0.3727          | 34.4346 |
| 0.2321        | 0.3577 | 2000 | 0.3637          | 33.5439 |
| 0.2396        | 0.4472 | 2500 | 0.3569          | 32.9164 |
| 0.2231        | 0.5366 | 3000 | 0.3512          | 33.0780 |
| 0.2039        | 0.6261 | 3500 | 0.3468          | 32.3184 |
| 0.2283        | 0.7155 | 4000 | 0.3430          | 31.7183 |


### Framework versions

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