---
library_name: transformers
language:
- multilingual
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- multilingual
metrics:
- wer
model-index:
- name: Whisper-Small-Multilingual-Uganda
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Bateesa/popolivoice, Bateesa/buaiir_voice_jap
      type: multilingual
      args: 'languages: japadhola, english; splits: train, test'
    metrics:
    - name: Wer
      type: wer
      value: 39.842067480258436
---

<!-- 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-Multilingual-Uganda

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Bateesa/popolivoice, Bateesa/buaiir_voice_jap dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7142
- Wer: 39.8421

## 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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0373        | 11.4943 | 1000 | 0.6213          | 29.6482 |
| 0.0125        | 22.9885 | 2000 | 0.6981          | 37.2577 |
| 0.0008        | 34.4828 | 3000 | 0.6874          | 39.6267 |
| 0.0007        | 45.9770 | 4000 | 0.7142          | 39.8421 |


### Framework versions

- Transformers 5.8.0
- Pytorch 2.11.0+cu130
- Datasets 2.21.0
- Tokenizers 0.22.2