---
language:
- yo
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Small Yo - Oyemade Oyemaja
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16
      type: mozilla-foundation/common_voice_16_1
      config: yo
      split: test
      args: yo
    metrics:
    - name: Wer
      type: wer
      value: 49.86116954143879
---

<!-- 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 Yo - Oyemade Oyemaja

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1731
- Wer Ortho: 70.4834
- Wer: 49.8612

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:-------:|
| 0.2595        | 3.8462  | 500  | 0.7546          | 71.3700   | 52.0488 |
| 0.0312        | 7.6923  | 1000 | 0.9057          | 74.6210   | 53.1174 |
| 0.0134        | 11.5385 | 1500 | 1.0199          | 72.2090   | 51.7711 |
| 0.0059        | 15.3846 | 2000 | 1.0713          | 71.2842   | 51.6281 |
| 0.0087        | 19.2308 | 2500 | 1.1007          | 70.5787   | 50.1136 |
| 0.006         | 23.0769 | 3000 | 1.1568          | 70.8552   | 50.6100 |
| 0.0059        | 26.9231 | 3500 | 1.1327          | 69.0438   | 48.4645 |
| 0.0043        | 30.7692 | 4000 | 1.1731          | 70.4834   | 49.8612 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1