---
language:
- ig
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small Igbo
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17
      type: mozilla-foundation/common_voice_17_0
      config: ig
      split: test
      args: ig
    metrics:
    - name: Wer
      type: wer
      value: 286.11111111111114
---

<!-- 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 Igbo

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17 dataset.
It achieves the following results on the evaluation set:
- Loss: 8.1870
- Wer Ortho: 294.2857
- Wer: 286.1111

## 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      |
|:-------------:|:------:|:----:|:---------------:|:---------:|:--------:|
| 0.0           | 500.0  | 500  | 3.2906          | 97.1429   | 88.8889  |
| 0.0           | 1000.0 | 1000 | 3.6536          | 91.4286   | 86.1111  |
| 0.0           | 1500.0 | 1500 | 4.3865          | 94.2857   | 91.6667  |
| 0.0           | 2000.0 | 2000 | 5.4348          | 102.8571  | 100.0    |
| 0.0           | 2500.0 | 2500 | 5.9169          | 94.2857   | 94.4444  |
| 0.0           | 3000.0 | 3000 | 6.6346          | 288.5714  | 277.7778 |
| 0.0           | 3500.0 | 3500 | 7.4267          | 297.1429  | 288.8889 |
| 0.0           | 4000.0 | 4000 | 8.1870          | 294.2857  | 286.1111 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1