metadata
language:
- ar
license: apache-2.0
base_model: deepdml/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- google/fleurs
- mozilla-foundation/common_voice_17_0
- UBC-NLP/Casablanca
- ymoslem/MediaSpeech
metrics:
- wer
model-index:
- name: Whisper Turbo ar
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: google/fleurs
config: ar
split: test
args: ar
metrics:
- name: Wer
type: wer
value: 13.800603776415219
Whisper Turbo ar
This model is a fine-tuned version of deepdml/whisper-large-v3-turbo on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 2.3375
- Wer: 13.8006
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4123 | 0.2 | 1000 | 2.2390 | 19.6509 |
| 0.2413 | 0.4 | 2000 | 2.3998 | 17.6051 |
| 0.1324 | 0.6 | 3000 | 2.3918 | 16.3601 |
| 0.0796 | 0.8 | 4000 | 2.3270 | 14.7044 |
| 0.0311 | 1.0 | 5000 | 2.3375 | 13.8006 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
Citation
@misc{deepdml/whisper-large-v3-turbo-ar-mix-norm,
title={Fine-tuned Whisper turbo ASR model for speech recognition in Arabic},
author={Jimenez, David},
howpublished={\url{https://huggingface.co/deepdml/whisper-large-v3-turbo-ar-mix-norm}},
year={2025}
}