metadata
datasets:
- mozilla-foundation/common_voice_11_0
language:
- ar
license: apache-2.0
metrics:
- wer
tags:
- whisper-event
- generated_from_trainer
- hf-asr-leaderboard
model-index:
- name: Whisper Small ar - Zaid Alyafeai
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0
type: mozilla-foundation/common_voice_11_0
config: ar
split: test
args: ar
metrics:
- type: wer
value: 22.38383004278958
name: Wer
Whisper Small ar - Zaid Alyafeai
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3509
- Wer: 22.3838
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: 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2944 | 0.2 | 1000 | 0.4355 | 30.6471 |
| 0.2671 | 0.4 | 2000 | 0.3786 | 25.8539 |
| 0.172 | 1.08 | 3000 | 0.3520 | 23.4573 |
| 0.1043 | 1.28 | 4000 | 0.3542 | 23.3278 |
| 0.0991 | 1.48 | 5000 | 0.3509 | 22.3838 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2