---
language:
- ig
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- deepdml/igbo-dict-16khz
- google/fleurs
- deepdml/igbo-dict-expansion-16khz
metrics:
- wer
model-index:
- name: Whisper Tiny ig
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs
      type: deepdml/igbo-dict-16khz
      config: ig_ng
      split: test
      args: ig_ng
    metrics:
    - name: Wer
      type: wer
      value: 60.390651571838106
---
<!-- 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 Tiny ig

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the google/fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2453
- Wer: 60.3907
- Cer: 25.7029

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.04
- training_steps: 5000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|
| 0.2001        | 1.0406 | 1000 | 0.9724          | 58.8455 | 24.7463 |
| 0.0942        | 2.0812 | 2000 | 1.0967          | 60.7065 | 24.6946 |
| 0.0633        | 3.1218 | 3000 | 1.1767          | 59.6472 | 24.2311 |
| 0.0417        | 5.003  | 4000 | 1.2294          | 60.0262 | 25.0141 |
| 0.0392        | 6.0436 | 5000 | 1.2453          | 60.3907 | 25.7029 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1

## Citation

Please cite the model using the following BibTeX entry:

```bibtex
@misc{deepdml/whisper-tiny-ig-mix-norm,
      title={Fine-tuned Whisper tiny ASR model for speech recognition in Lingala},
      author={Jimenez, David},
      howpublished={\url{https://huggingface.co/deepdml/whisper-tiny-ig-mix-norm}},
      year={2025}
    }
```