metadata
language:
- af
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Tiny af
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Fleurs
type: google/fleurs
config: af_za
split: test
args: af_za
metrics:
- name: Wer
type: wer
value: 49.523809523809526
Whisper Tiny af
This model is a fine-tuned version of openai/whisper-tiny on the Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 1.2862
- Wer: 49.5238
- Cer: 21.6345
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: 64
- eval_batch_size: 64
- 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: 600
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.9449 | 3.0017 | 100 | 1.3743 | 55.2381 | 21.4644 |
| 0.4604 | 6.0033 | 200 | 1.2738 | 51.1515 | 20.4000 |
| 0.2774 | 9.005 | 300 | 1.2614 | 49.8528 | 20.9014 |
| 0.1969 | 12.0067 | 400 | 1.2717 | 50.2857 | 21.6315 |
| 0.1467 | 15.0083 | 500 | 1.2801 | 49.7662 | 21.5113 |
| 0.1375 | 18.01 | 600 | 1.2862 | 49.5238 | 21.6345 |
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:
@misc{deepdml/whisper-tiny-af-fleurs-norm,
title={Fine-tuned Whisper tiny ASR model for speech recognition in Afrikaans},
author={Jimenez, David},
howpublished={\url{https://huggingface.co/deepdml/whisper-tiny-af-fleurs-norm}},
year={2026}
}