---
library_name: transformers
language:
- yo
license: apache-2.0
base_model: EYEDOL/whisper-tiny-yoruba
tags:
- generated_from_trainer
datasets:
- EYEDOL/naija-voices-yoruba-split_0-1
metrics:
- wer
model-index:
- name: EYEDOL/whisper-tiny-yoruba
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: EYEDOL/naija-voices-yoruba-split_0-1
      type: EYEDOL/naija-voices-yoruba-split_0-1
    metrics:
    - name: Wer
      type: wer
      value: 0.7006286797724778
---

<!-- 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-yoruba

This model is a fine-tuned version of [EYEDOL/whisper-tiny-yoruba](https://huggingface.co/EYEDOL/whisper-tiny-yoruba) on the EYEDOL/naija-voices-yoruba-split_0-1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8526
- Wer Ortho: 0.7773
- Wer: 0.7006

## 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: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 1.7353        | 1.0   | 583  | 0.8680          | 0.9448    | 0.8654 |
| 1.6436        | 2.0   | 1166 | 0.8494          | 0.8213    | 0.7490 |
| 1.5173        | 3.0   | 1749 | 0.8319          | 0.8237    | 0.7470 |
| 1.4143        | 4.0   | 2332 | 0.8215          | 0.7845    | 0.7128 |
| 1.3252        | 5.0   | 2915 | 0.8135          | 0.8788    | 0.7910 |
| 1.2425        | 6.0   | 3498 | 0.8106          | 0.7988    | 0.7224 |
| 1.1664        | 7.0   | 4081 | 0.8118          | 0.8508    | 0.7635 |
| 1.0950        | 8.0   | 4664 | 0.8156          | 0.7628    | 0.6813 |
| 1.0273        | 9.0   | 5247 | 0.8191          | 0.7867    | 0.7204 |
| 0.9611        | 10.0  | 5830 | 0.8292          | 0.7736    | 0.6948 |
| 0.8975        | 11.0  | 6413 | 0.8353          | 0.8007    | 0.7126 |
| 0.8363        | 12.0  | 6996 | 0.8526          | 0.7773    | 0.7006 |


### Framework versions

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