metadata
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small AR
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: ar
split: None
args: 'config: ar_de, split: test'
metrics:
- name: Wer
type: wer
value: 44.396092688480046
Whisper Small Arabic
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3517
- Wer: 44.3961
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2707 | 0.4119 | 1000 | 0.4188 | 51.3000 |
| 0.2452 | 0.8237 | 2000 | 0.3639 | 46.1863 |
| 0.1613 | 1.2356 | 3000 | 0.3470 | 44.9194 |
| 0.1382 | 1.6474 | 4000 | 0.3398 | 45.0351 |
| 0.1177 | 2.0593 | 5000 | 0.3502 | 44.5154 |
| 0.1206 | 2.4712 | 6000 | 0.3501 | 44.9781 |
| 0.1216 | 2.8830 | 7000 | 0.3423 | 43.5258 |
| 0.072 | 3.2949 | 8000 | 0.3517 | 44.3961 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0