---
library_name: transformers
language:
- yo
license: apache-2.0
base_model: EYEDOL/whisper-tiny-yoruba2
tags:
- generated_from_trainer
datasets:
- EYEDOL/naija-voices-yoruba-split_0-6
metrics:
- wer
model-index:
- name: EYEDOL/whisper-tiny-yoruba3
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: EYEDOL/naija-voices-yoruba-split_0-6
      type: EYEDOL/naija-voices-yoruba-split_0-6
    metrics:
    - name: Wer
      type: wer
      value: 0.6293283063796011
---

<!-- 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. -->

# EYEDOL/whisper-tiny-yoruba3

This model is a fine-tuned version of [EYEDOL/whisper-tiny-yoruba2](https://huggingface.co/EYEDOL/whisper-tiny-yoruba2) on the EYEDOL/naija-voices-yoruba-split_0-6 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7111
- Wer Ortho: 0.7096
- Wer: 0.6293

## 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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 1.4417        | 1.0   | 583  | 0.7132          | 0.7172    | 0.6352 |
| 1.3179        | 2.0   | 1166 | 0.7039          | 0.6964    | 0.6110 |
| 1.2151        | 3.0   | 1749 | 0.7038          | 0.7101    | 0.6275 |
| 1.1268        | 4.0   | 2332 | 0.7058          | 0.7037    | 0.6166 |
| 1.0504        | 5.0   | 2915 | 0.7111          | 0.7096    | 0.6293 |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2