---
language:
- nyn
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- tericlabs
metrics:
- wer
model-index:
- name: Whisper Small Runyankore
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Yogera data
      type: tericlabs
    metrics:
    - name: Wer
      type: wer
      value: 47.48073503260225
---

<!-- 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 Runyankore

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Yogera data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6975
- Wer: 47.4807

## 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: 1000
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 3.7277        | 0.43  | 100  | 2.6880          | 98.2810 |
| 2.265         | 0.85  | 200  | 1.8155          | 84.8251 |
| 1.6872        | 1.28  | 300  | 1.3734          | 75.1630 |
| 1.25          | 1.7   | 400  | 0.9704          | 65.2638 |
| 0.9047        | 2.13  | 500  | 0.8496          | 57.9727 |
| 0.7852        | 2.55  | 600  | 0.7705          | 57.0836 |
| 0.7065        | 2.98  | 700  | 0.7080          | 51.4523 |
| 0.4952        | 3.4   | 800  | 0.6939          | 50.3853 |
| 0.516         | 3.83  | 900  | 0.6786          | 49.0219 |
| 0.4005        | 4.26  | 1000 | 0.6975          | 47.4807 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0