metadata
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- private
metrics:
- wer
model-index:
- name: Whisper base ar - Mohamed Ahmed-Mahmoud Nasser
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: private
type: private
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 18.308400460299197
Whisper base ar - Mohamed Ahmed-Mahmoud Nasser
This model is a fine-tuned version of openai/whisper-base on the private dataset. It achieves the following results on the evaluation set:
- Loss: 0.1244
- Wer: 18.3084
- Cer: 8.3096
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- training_steps: 6000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.107 | 1.0638 | 1000 | 0.1412 | 26.0759 | 10.2741 |
| 0.0927 | 2.1277 | 2000 | 0.1159 | 21.8412 | 9.1956 |
| 0.0601 | 3.1915 | 3000 | 0.1155 | 22.0368 | 9.2820 |
| 0.042 | 4.2553 | 4000 | 0.1135 | 18.7112 | 8.3240 |
| 0.018 | 5.3191 | 5000 | 0.1226 | 17.9517 | 8.1499 |
| 0.0068 | 6.3830 | 6000 | 0.1244 | 18.3084 | 8.3096 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.2
- Tokenizers 0.21.0