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 - full
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: 121.00549461448435
QURANIC Whisper Large V3 - full
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: 0.0375
- Wer: 121.0055
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: 4
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|
| 0.1349 | 0.2 | 1000 | 0.1227 | 256.8256 |
| 0.1098 | 0.4 | 2000 | 0.0918 | 438.2193 |
| 0.1071 | 0.6 | 3000 | 0.0839 | 286.1663 |
| 0.0837 | 0.8 | 4000 | 0.0737 | 295.5091 |
| 0.0672 | 1.0 | 5000 | 0.0611 | 293.6147 |
| 0.03 | 1.2 | 6000 | 0.0559 | 204.9680 |
| 0.0104 | 1.4 | 7000 | 0.0485 | 189.5761 |
| 0.0245 | 1.6 | 8000 | 0.0456 | 141.0698 |
| 0.0446 | 1.8 | 9000 | 0.0398 | 134.5774 |
| 0.0231 | 2.0 | 10000 | 0.0375 | 121.0055 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.0
- Datasets 2.18.0
- Tokenizers 0.15.1