--- language: - ar license: apache-2.0 tags: - whisper-event - generated_from_trainer - hf-asr-leaderboard datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper Small ar - Zaid Alyafeai results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_11_0 type: mozilla-foundation/common_voice_11_0 config: ar split: test args: ar metrics: - name: Wer type: wer value: 22.38383004278958 --- # Whisper Small ar - Zaid Alyafeai This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.3509 - Wer: 22.3838 ## 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: 8 - eval_batch_size: 4 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.2944 | 0.2 | 1000 | 0.4355 | 30.6471 | | 0.2671 | 0.4 | 2000 | 0.3786 | 25.8539 | | 0.172 | 1.08 | 3000 | 0.3520 | 23.4573 | | 0.1043 | 1.28 | 4000 | 0.3542 | 23.3278 | | 0.0991 | 1.48 | 5000 | 0.3509 | 22.3838 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0+cu116 - Datasets 2.7.1 - Tokenizers 0.13.2