metadata
language:
- ig
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- deepdml/igbo-dict-expansion-16khz
- google/fleurs
- deepdml/igbo-dict-16khz
metrics:
- wer
model-index:
- name: Whisper Medium ig
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: google/fleurs
type: deepdml/igbo-dict-expansion-16khz
config: ig_ng
split: test
args: ig_ng
metrics:
- name: Wer
type: wer
value: 39.40041786113406
Whisper Medium ig
This model is a fine-tuned version of openai/whisper-medium on the google/fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.8789
- Wer: 39.4004
- Cer: 12.6049
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: 32
- 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: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.107 | 0.2 | 1000 | 0.6957 | 43.6179 | 14.1782 |
| 0.0471 | 0.4 | 2000 | 0.7596 | 39.8086 | 12.9539 |
| 0.0273 | 0.6 | 3000 | 0.8375 | 40.2070 | 12.8450 |
| 0.0077 | 1.163 | 4000 | 0.8775 | 39.8814 | 12.8099 |
| 0.0149 | 1.363 | 5000 | 0.8789 | 39.4004 | 12.6049 |
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-ig-mix-norm,
title={Fine-tuned Whisper medium ASR model for speech recognition in Lingala},
author={Jimenez, David},
howpublished={\url{https://huggingface.co/deepdml/whisper-medium-ig-mix-norm}},
year={2025}
}