metadata
language:
- ar
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Arabic
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 ar
type: mozilla-foundation/common_voice_11_0
config: ar
split: test
args: ar
metrics:
- name: Wer
type: wer
value: 54.08
Whisper Small Arabic
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 ar dataset. It achieves the following results on the evaluation set:
- Loss: 0.4948
- Wer: 54.08
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: 32
- eval_batch_size: 2
- 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: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1885 | 1.03 | 1000 | 0.3950 | 66.44 |
| 0.0794 | 3.0 | 2000 | 0.3950 | 58.5507 |
| 0.0286 | 4.04 | 3000 | 0.4602 | 63.88 |
| 0.0128 | 6.01 | 4000 | 0.4948 | 54.08 |
| 0.0048 | 7.04 | 5000 | 0.5466 | 57.9867 |
| 0.0029 | 9.01 | 6000 | 0.5710 | 55.4147 |
| 0.0013 | 10.05 | 7000 | 0.5996 | 58.7707 |
| 0.0008 | 12.02 | 8000 | 0.6179 | 54.748 |
| 0.0006 | 13.05 | 9000 | 0.6343 | 56.2613 |
| 0.0003 | 15.02 | 10000 | 0.6388 | 56.228 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.1.dev0
- Tokenizers 0.13.2