metadata
language:
- af
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Medium 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: 24.12121212121212
Whisper Medium af
This model is a fine-tuned version of openai/whisper-medium on the Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.6584
- Wer: 24.1212
- Cer: 9.2133
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: linear
- lr_scheduler_warmup_ratio: 0.04
- training_steps: 600
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.322 | 0.1667 | 100 | 0.6194 | 25.8355 | 9.9346 |
| 0.0922 | 1.1183 | 200 | 0.6106 | 25.8528 | 10.0431 |
| 0.0363 | 2.07 | 300 | 0.6271 | 24.5714 | 10.3715 |
| 0.019 | 3.0217 | 400 | 0.6469 | 24.8831 | 10.5211 |
| 0.011 | 3.1883 | 500 | 0.6518 | 27.1861 | 11.8553 |
| 0.0056 | 4.14 | 600 | 0.6584 | 24.1212 | 9.2133 |
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-medium-af-fleurs-norm,
title={Fine-tuned Whisper medium ASR model for speech recognition in Afrikaans},
author={Jimenez, David},
howpublished={\url{https://huggingface.co/deepdml/whisper-medium-af-fleurs-norm}},
year={2026}
}