--- language: - ar license: apache-2.0 base_model: openai/whisper-small tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_16_0 metrics: - wer model-index: - name: Whisper Small ar - majed test results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 16.0 type: mozilla-foundation/common_voice_16_0 config: ar split: test args: 'config: ar, split: test' metrics: - name: Wer type: wer value: 260.25560867966163 --- # Whisper Small ar - majed test This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.3249 - Wer: 260.2556 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.3013 | 0.41 | 1000 | 0.4102 | 337.6793 | | 0.2533 | 0.82 | 2000 | 0.3525 | 344.5476 | | 0.1632 | 1.24 | 3000 | 0.3397 | 278.4185 | | 0.1526 | 1.65 | 4000 | 0.3249 | 260.2556 | ### Framework versions - Transformers 4.36.2 - Pytorch 2.1.2 - Datasets 2.16.1 - Tokenizers 0.15.0