This model is a fine-tuned version of openai/whisper-base on the Common Voice 11.0 - Arabic dataset. It achieves the following results on the evaluation set:

Loss: 1.6060
Wer: 64.0180

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: 6
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
0.0051	22.22	1000	1.3485	66.5792
0.0003	44.44	2000	1.5180	62.4313
0.0002	66.67	3000	1.5829	63.3683
0.0001	88.89	4000	1.6060	64.0180

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Tokenizers 0.15.1

naiftamia/whisper-small-Withaq

Whisper small withaq - T5SA

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

naiftamia/
whisper-small-Withaq