---
language:
- sw
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Swahili - Badili
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13.0
      type: mozilla-foundation/common_voice_13_0
      config: sw
      split: test
      args: 'config: sw, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 98.40119332745073
---

<!-- 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 Swahili - Badili

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 13.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4329
- Wer: 98.4012

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 12000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer      |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3563        | 0.35  | 1000  | 0.4938          | 100.5715 |
| 0.2853        | 0.69  | 2000  | 0.4143          | 100.7007 |
| 0.1612        | 1.04  | 3000  | 0.3910          | 100.9748 |
| 0.1399        | 1.38  | 4000  | 0.3762          | 98.4989  |
| 0.1657        | 1.73  | 5000  | 0.3700          | 90.3357  |
| 0.0818        | 2.08  | 6000  | 0.3775          | 98.0493  |
| 0.0749        | 2.42  | 7000  | 0.3768          | 97.9936  |
| 0.0637        | 2.77  | 8000  | 0.3822          | 92.9440  |
| 0.0355        | 3.11  | 9000  | 0.4036          | 93.8979  |
| 0.0299        | 3.46  | 10000 | 0.4141          | 97.9695  |
| 0.0277        | 3.8   | 11000 | 0.4175          | 98.2961  |
| 0.0147        | 4.15  | 12000 | 0.4329          | 98.4012  |


### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3