whisper-small-ar-v2

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whisper-small-ar-v2

This model is for Arabic automatic speech recognition (ASR). It is a fine-tuned version of openai/whisper-small on the Arabic portion of the mozilla-foundation/common_voice_16_1 dataset. It achieves the following results on the evaluation set:

• Loss: 0.4007
• Wer: 47.7264

Model description

Whisper model fine-tuned on Arabic data, following the official tutorial.

Intended uses & limitations

It is recommended to fine-tune and evaluate on your data before using it.

Training and evaluation data

Training Data: CommonVoice (v16.1) Arabic train + validation splits
Validation Data: CommonVoice (v16.1) Arabic test split

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 32
• eval_batch_size: 32
• 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: 8000
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.38.1
• Pytorch 2.1.0+cu118
• Datasets 2.17.1
• Tokenizers 0.15.2