This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset For short transcription 30s but for long transcription it has some limitations and challenges. It achieves the following results on the evaluation set:

Loss: 0.3791
Wer: 49.8081

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: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0972	0.57	1000	0.3791	49.8081
0.0978	1.14	2000	0.3791	49.8081
0.0986	1.71	3000	0.3791	49.8081
0.1055	2.28	4000	0.3791	49.8081

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.0+cu116
Datasets 2.8.0
Tokenizers 0.13.2

Abdo96/whisper-small-ar

Whisper Small Ar - Abdallah Elbohy

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Abdo96/
whisper-small-ar