metadata
library_name: transformers
language:
- ar
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- EMahdi/WhisperFinetune
metrics:
- wer
model-index:
- name: Whisper Large V3 Turbo Finetune Ar - EMahdi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: EMahdi/WhisperFinetune Sudanese Corpus
type: EMahdi/WhisperFinetune
args: 'config: sudanese_corpus, split: test'
metrics:
- name: Wer
type: wer
value: 42.80180761781795
Whisper Large V3 Turbo Finetune Ar - EMahdi
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the EMahdi/WhisperFinetune Sudanese Corpus dataset. It achieves the following results on the evaluation set:
- Loss: 0.8721
- Wer: 42.8018
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_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.2464 | 1.0 | 89 | 0.9025 | 71.2072 |
| 0.7343 | 2.0 | 178 | 0.7835 | 55.7779 |
| 0.5441 | 3.0 | 267 | 0.7463 | 56.3105 |
| 0.4076 | 4.0 | 356 | 0.7532 | 47.5468 |
| 0.325 | 5.0 | 445 | 0.7811 | 51.4526 |
| 0.2635 | 6.0 | 534 | 0.8050 | 62.1369 |
| 0.1866 | 7.0 | 623 | 0.8226 | 45.7715 |
| 0.1171 | 8.0 | 712 | 0.8406 | 45.4810 |
| 0.0679 | 9.0 | 801 | 0.8664 | 43.5119 |
| 0.0399 | 10.0 | 890 | 0.8721 | 42.8018 |
Framework versions
- Transformers 4.45.0
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3