metadata
language:
- ar
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small ar1 - Mohamed Shaaban
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common standard ar Voice 11.0
type: mozilla-foundation/common_voice_11_0
metrics:
- name: Wer
type: wer
value: 65.27199999999999
Whisper Small ar1 - Mohamed Shaaban
This model is a fine-tuned version of openai/whisper-base on the Common standard ar Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4585
- Wer: 65.2720
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.444 | 0.42 | 1000 | 0.5684 | 73.7587 |
| 0.4161 | 0.83 | 2000 | 0.4995 | 68.0147 |
| 0.3282 | 1.25 | 3000 | 0.4841 | 68.92 |
| 0.2915 | 1.66 | 4000 | 0.4663 | 67.6120 |
| 0.2639 | 2.08 | 5000 | 0.4585 | 65.2720 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2