YazanSalameh/Whisper-base-Arabic

Whisper base arabic

It achieves the following results on the evaluation set:

• Loss: 0.44
• Wer: 34.7

Training and evaluation data

Train set:

• mozilla-foundation/common_voice_16_0 ar [train+validation]
• BelalElhossany/mgb2_audios_transcriptions_non_overlap
• nadsoft/Jordan-Audio

cross validation set: 600 samples in total from the 3 sets to save time during training as colab free tier was used to train the model. note: evaluate accuracy in the way you see fit.

Training procedure

removed arabic (حركات) from the texts. trained the model on the combined dataset for 6 epochs, the best one being the fifth so the model is basically the 5th epoch.

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 32
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 1
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.4603	1	1437	0.4931	45.8857
0.2867	2	2874	0.4493	36.9973
0.2494	3	4311	0.4219	43.5553
0.1435	4	5748	0.4408	40.2351
0.1345	5	7185	0.4407	34.7081