metadata
language:
- ar
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- ahishamm/QURANICWhisperDataset
metrics:
- wer
model-index:
- name: QURANIC Whisper Large V3 - 10000
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: QURANICWhisperDataset
type: ahishamm/QURANICWhisperDataset
args: 'config: ar, split: train'
metrics:
- name: Wer
type: wer
value: 99.93905329450803
QURANIC Whisper Large V3 - 10000
This model is a fine-tuned version of openai/whisper-large-v3 on the QURANICWhisperDataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.2528
- Wer: 99.9391
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: 8
- 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: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0907 | 2.0 | 1000 | 0.1326 | 107.4287 |
| 0.0545 | 4.0 | 2000 | 0.1366 | 156.4231 |
| 0.0211 | 6.0 | 3000 | 0.1515 | 245.3308 |
| 0.0076 | 8.0 | 4000 | 0.1627 | 330.6630 |
| 0.0031 | 10.0 | 5000 | 0.1788 | 170.7794 |
| 0.0035 | 12.0 | 6000 | 0.1947 | 107.0630 |
| 0.0006 | 14.0 | 7000 | 0.2107 | 98.0091 |
| 0.0 | 16.0 | 8000 | 0.2208 | 97.8533 |
| 0.0 | 18.0 | 9000 | 0.2426 | 99.7833 |
| 0.0 | 20.0 | 10000 | 0.2528 | 99.9391 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.0
- Datasets 2.18.0
- Tokenizers 0.15.1