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 Large 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: 49.431999999999995
Whisper Large Arabic
This model is a fine-tuned version of openai/whisper-large on the mozilla-foundation/common_voice_11_0 ar dataset. It achieves the following results on the evaluation set:
- Loss: 0.3231
- Wer: 49.4320
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: 8
- 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 |
|---|---|---|---|---|
| 0.2472 | 0.1 | 1000 | 0.3719 | 58.9560 |
| 0.2015 | 0.2 | 2000 | 0.3487 | 53.5213 |
| 0.1418 | 1.04 | 3000 | 0.3231 | 49.4320 |
| 0.0921 | 1.14 | 4000 | 0.3284 | 56.1107 |
| 0.0923 | 1.24 | 5000 | 0.3304 | 61.4227 |
| 0.0483 | 2.08 | 6000 | 0.3460 | 55.952 |
| 0.0391 | 2.18 | 7000 | 0.3538 | 51.1067 |
| 0.0228 | 3.02 | 8000 | 0.3493 | 51.82 |
| 0.0206 | 3.12 | 9000 | 0.3729 | 52.4000 |
| 0.018 | 3.22 | 10000 | 0.3676 | 51.296 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.1.dev0
- Tokenizers 0.13.2