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 Medium 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: 47.53066666666667
Whisper Medium Arabic
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0 ar dataset. It achieves the following results on the evaluation set:
- Loss: 0.4218
- Wer: 47.5307
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: 4
- 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 |
|---|---|---|---|---|
| 0.2215 | 0.1 | 1000 | 0.3361 | 49.9307 |
| 0.1134 | 1.07 | 2000 | 0.3290 | 56.76 |
| 0.0765 | 2.04 | 3000 | 0.3400 | 54.3947 |
| 0.0417 | 3.01 | 4000 | 0.3599 | 52.5320 |
| 0.0364 | 3.11 | 5000 | 0.3740 | 55.5653 |
| 0.0094 | 4.08 | 6000 | 0.4152 | 56.4307 |
| 0.0077 | 5.05 | 7000 | 0.4218 | 47.5307 |
| 0.0018 | 6.02 | 8000 | 0.4556 | 50.0493 |
| 0.0012 | 6.12 | 9000 | 0.4760 | 54.8147 |
| 0.0009 | 7.09 | 10000 | 0.4711 | 48.7533 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.1.dev0
- Tokenizers 0.13.2