---
language:
- ig
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small Igbo
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs-jboat
      type: google/fleurs
      config: ig_ng
      split: test
      args: ig_ng
    metrics:
    - name: Wer
      type: wer
      value: 44.01272438082254
---

<!-- 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 google/fleurs-jboat dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0619
- Wer Ortho: 47.8937
- Wer: 44.0127

## 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     |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:-------:|
| 0.3161        | 2.6455  | 500  | 0.7413          | 50.2340   | 46.1448 |
| 0.0421        | 5.2910  | 1000 | 0.8582          | 49.0269   | 44.8004 |
| 0.0168        | 7.9365  | 1500 | 0.9246          | 47.6351   | 43.5204 |
| 0.0075        | 10.5820 | 2000 | 0.9912          | 47.7541   | 43.3121 |
| 0.0051        | 13.2275 | 2500 | 1.0277          | 47.7377   | 43.3954 |
| 0.0067        | 15.8730 | 3000 | 1.0354          | 47.6638   | 43.1644 |
| 0.0041        | 18.5185 | 3500 | 1.0722          | 48.3864   | 44.1112 |
| 0.0028        | 21.1640 | 4000 | 1.0619          | 47.8937   | 44.0127 |


### Framework versions

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