metadata
language:
- ar
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- ahishamm/whisperQURANIC
metrics:
- wer
model-index:
- name: QURANIC Whisper Large V3
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: whisperQURANIC
type: ahishamm/whisperQURANIC
args: 'config: ar, split: train'
metrics:
- name: Wer
type: wer
value: 268.8141178069162
QURANIC Whisper Large V3
This model is a fine-tuned version of openai/whisper-large-v3 on the whisperQURANIC dataset. It achieves the following results on the evaluation set:
- Loss: 0.0238
- Wer: 268.8141
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: 1
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1467 | 0.4 | 200 | 0.1302 | 42.9071 |
| 0.1226 | 0.8 | 400 | 0.0958 | 156.6683 |
| 0.0746 | 1.2 | 600 | 0.0772 | 494.4510 |
| 0.0868 | 1.6 | 800 | 0.0678 | 252.8552 |
| 0.0801 | 2.0 | 1000 | 0.0560 | 361.0673 |
| 0.0552 | 2.4 | 1200 | 0.0473 | 153.8658 |
| 0.053 | 2.8 | 1400 | 0.0399 | 310.5204 |
| 0.0421 | 3.2 | 1600 | 0.0308 | 305.3961 |
| 0.0291 | 3.6 | 1800 | 0.0266 | 242.5182 |
| 0.0303 | 4.0 | 2000 | 0.0238 | 268.8141 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.0
- Datasets 2.18.0
- Tokenizers 0.15.1