|
--- |
|
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 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# Whisper Large ArabicEnglish - Mostafa Khedr |
|
|
|
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/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 |
|
|
