---
language:
- yo
license: apache-2.0
base_model: EYEDOL/Yoruba-ASR2
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: YorubaASR3
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: yo
      split: None
      args: yo
    metrics:
    - name: Wer
      type: wer
      value: 42.30348886086591
---

<!-- 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. -->

# YorubaASR3

This model is a fine-tuned version of [EYEDOL/Yoruba-ASR2](https://huggingface.co/EYEDOL/Yoruba-ASR2) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0831
- Wer: 42.3035

## 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: 8
- 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0001        | 15.3846 | 4000 | 1.0831          | 42.3035 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 3.2.0
- Tokenizers 0.19.1