---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- babs/nigerian-accented-english
metrics:
- wer
model-index:
- name: Whisper Small english - Nigerian accent
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Nigerian accented english
      type: babs/nigerian-accented-english
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 48.805954719321825
---

<!-- 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 english - Nigerian accent

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Nigerian accented english dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3324
- Wer: 48.8060

## 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: 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     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.3217        | 4.6948  | 1000 | 0.8267          | 55.4637 |
| 0.0653        | 9.3897  | 2000 | 1.0964          | 53.9440 |
| 0.0161        | 14.0845 | 3000 | 1.2460          | 51.9901 |
| 0.0044        | 18.7793 | 4000 | 1.3324          | 48.8060 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0