metadata
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
Whisper Tiny ig
This model is a fine-tuned version of 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:
@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}
}