metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
datasets:
- MohamedRashad/arabic-english-code-switching
metrics:
- wer
model-index:
- name: Whisper Large ArabicEnglish - Mostafa Khedr
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: arabic-english-code-switching
type: MohamedRashad/arabic-english-code-switching
metrics:
- name: Wer
type: wer
value: 31.61836083760921
Whisper Large ArabicEnglish - Mostafa Khedr
This model is a fine-tuned version of openai/whisper-large-v2 on the arabic-english-code-switching dataset. It achieves the following results on the evaluation set:
- Loss: 0.7108
- Wer: 31.6184
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: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|---|---|---|---|---|
| 0.558 | 0.6748 | 1000 | 0.5802 | 46.1378 |
| 0.3725 | 1.3495 | 2000 | 0.5258 | 43.1008 |
| 0.2131 | 2.0243 | 3000 | 0.5152 | 34.4890 |
| 0.204 | 2.6991 | 4000 | 0.5111 | 37.8727 |
| 0.1012 | 3.3738 | 5000 | 0.5475 | 34.1839 |
| 0.0593 | 4.0486 | 6000 | 0.5693 | 33.2686 |
| 0.0436 | 4.7233 | 7000 | 0.5895 | 33.0190 |
| 0.0189 | 5.3981 | 8000 | 0.6472 | 31.9235 |
| 0.0063 | 6.0729 | 9000 | 0.6850 | 32.2701 |
| 0.0046 | 6.7476 | 10000 | 0.7108 | 31.6184 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3