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: 22.232451093210585
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: 0.1082
- Wer: 22.2325
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: 16
- eval_batch_size: 8
- 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: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2541 | 0.5319 | 500 | 0.2250 | 44.5224 |
| 0.1526 | 1.0638 | 1000 | 0.1526 | 31.0242 |
| 0.1344 | 1.5957 | 1500 | 0.1321 | 27.8826 |
| 0.1217 | 2.1277 | 2000 | 0.1197 | 24.7066 |
| 0.1044 | 2.6596 | 2500 | 0.1153 | 23.7975 |
| 0.0886 | 3.1915 | 3000 | 0.1140 | 23.9471 |
| 0.1053 | 3.7234 | 3500 | 0.1090 | 22.3245 |
| 0.0843 | 4.2553 | 4000 | 0.1082 | 22.2325 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.2
- Tokenizers 0.21.0