metadata
language:
- ar
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-small
datasets:
- zolfa
metrics:
- wer
model-index:
- name: Zolfa-raghadomar
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Zolfa Dataset
type: zolfa
args: 'config: ar, split: test'
metrics:
- type: wer
value: 8.571428571428571
name: Wer
Zolfa-raghadomar
This model is a fine-tuned version of openai/whisper-small on the Zolfa Dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.2396
- Wer: 8.5714
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: 4
- 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: 5
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0673 | 0.6993 | 100 | 0.2047 | 12.8571 |
| 0.0239 | 1.3986 | 200 | 0.2376 | 10.4082 |
| 0.0087 | 2.0979 | 300 | 0.2165 | 9.7959 |
| 0.009 | 2.7972 | 400 | 0.2169 | 7.9592 |
| 0.0034 | 3.4965 | 500 | 0.2277 | 8.5714 |
| 0.0041 | 4.1958 | 600 | 0.2401 | 8.5714 |
| 0.0032 | 4.8951 | 700 | 0.2395 | 7.9592 |
| 0.0007 | 5.5944 | 800 | 0.2430 | 8.5714 |
| 0.0002 | 6.2937 | 900 | 0.2380 | 8.5714 |
| 0.0015 | 6.9930 | 1000 | 0.2396 | 8.5714 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1