metadata
language:
- af
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Base 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: 42.008658008658
Whisper Base af
This model is a fine-tuned version of openai/whisper-base on the Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 1.1171
- Wer: 42.0087
- Cer: 18.5731
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 |
|---|---|---|---|---|---|
| 0.6138 | 3.0017 | 100 | 1.0982 | 48.7792 | 19.1919 |
| 0.2216 | 6.0033 | 200 | 1.0553 | 43.0303 | 17.0425 |
| 0.0984 | 9.005 | 300 | 1.0633 | 44.5195 | 19.8927 |
| 0.0527 | 12.0067 | 400 | 1.0950 | 45.1429 | 19.2446 |
| 0.0325 | 15.0083 | 500 | 1.1121 | 41.8182 | 16.4179 |
| 0.0291 | 18.01 | 600 | 1.1171 | 42.0087 | 18.5731 |
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-base-af-fleurs-norm,
title={Fine-tuned Whisper base ASR model for speech recognition in Afrikaans},
author={Jimenez, David},
howpublished={\url{https://huggingface.co/deepdml/whisper-base-af-fleurs-norm}},
year={2026}
}