---
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: 20.96195262024408
---

<!-- 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: 0.7019
- Wer: 20.9620

## 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: 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: 100
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 1.0917        | 2.2989  | 200  | 0.4674          | 24.6231 |
| 0.4938        | 4.5977  | 400  | 0.5308          | 21.3927 |
| 0.2699        | 6.8966  | 600  | 0.5277          | 22.6849 |
| 0.1000        | 9.1954  | 800  | 0.6029          | 21.8234 |
| 0.0515        | 11.4943 | 1000 | 0.6263          | 23.9770 |
| 0.0196        | 13.7931 | 1200 | 0.6510          | 20.6748 |
| 0.0034        | 16.0920 | 1400 | 0.6879          | 20.8902 |
| 0.0035        | 17.2414 | 1500 | 0.7019          | 20.9620 |


### Framework versions

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