---
library_name: transformers
language:
- yo
license: apache-2.0
base_model: EYEDOL/whisper-tiny-yoruba1
tags:
- generated_from_trainer
datasets:
- EYEDOL/naija-voices-yoruba-split_0-5
metrics:
- wer
model-index:
- name: EYEDOL/whisper-tiny-yoruba2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: EYEDOL/naija-voices-yoruba-split_0-5
      type: EYEDOL/naija-voices-yoruba-split_0-5
    metrics:
    - name: Wer
      type: wer
      value: 0.6604725510764774
---

<!-- 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-yoruba2

This model is a fine-tuned version of [EYEDOL/whisper-tiny-yoruba1](https://huggingface.co/EYEDOL/whisper-tiny-yoruba1) on the EYEDOL/naija-voices-yoruba-split_0-5 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8206
- Wer Ortho: 0.7328
- Wer: 0.6605

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 1.4647        | 1.0   | 583  | 0.7470          | 0.7172    | 0.6312 |
| 1.4031        | 2.0   | 1166 | 0.7409          | 0.7386    | 0.6564 |
| 1.3010        | 3.0   | 1749 | 0.7406          | 0.7229    | 0.6421 |
| 1.2136        | 4.0   | 2332 | 0.7384          | 0.7477    | 0.6644 |
| 1.1362        | 5.0   | 2915 | 0.7413          | 0.7877    | 0.7124 |
| 1.0626        | 6.0   | 3498 | 0.7462          | 0.7162    | 0.6332 |
| 0.9947        | 7.0   | 4081 | 0.7573          | 0.7547    | 0.6707 |
| 0.9314        | 8.0   | 4664 | 0.7624          | 0.7062    | 0.6266 |
| 0.8680        | 9.0   | 5247 | 0.7747          | 0.7211    | 0.6416 |
| 0.8080        | 10.0  | 5830 | 0.7881          | 0.7519    | 0.6641 |
| 0.7481        | 11.0  | 6413 | 0.8032          | 0.7310    | 0.6519 |
| 0.6922        | 12.0  | 6996 | 0.8206          | 0.7328    | 0.6605 |


### Framework versions

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