---
base_model: mbazaNLP/Whisper-Small-Kinyarwanda
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: whisper-small-rw
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_11_0
      type: common_voice_11_0
      config: rw
      split: None
      args: rw
    metrics:
    - name: Wer
      type: wer
      value: 33.420365535248045
---

<!-- 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-rw

This model is a fine-tuned version of [mbazaNLP/Whisper-Small-Kinyarwanda](https://huggingface.co./mbazaNLP/Whisper-Small-Kinyarwanda) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0954
- Wer: 33.4204

## 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: 5
- training_steps: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| No log        | 1.4286  | 10   | 2.3900          | 34.2037 |
| No log        | 2.8571  | 20   | 2.3111          | 34.5953 |
| 2.1422        | 4.2857  | 30   | 2.2492          | 34.2037 |
| 2.1422        | 5.7143  | 40   | 2.2022          | 33.9426 |
| 1.8742        | 7.1429  | 50   | 2.1669          | 33.8120 |
| 1.8742        | 8.5714  | 60   | 2.1406          | 33.6815 |
| 1.8742        | 10.0    | 70   | 2.1216          | 33.4204 |
| 1.7608        | 11.4286 | 80   | 2.1077          | 33.2898 |
| 1.7608        | 12.8571 | 90   | 2.0994          | 33.5509 |
| 1.6573        | 14.2857 | 100  | 2.0954          | 33.4204 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1