--- language: - ar license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper Small Ar - Neethu VM results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 11.0 type: mozilla-foundation/common_voice_11_0 config: ar split: test args: 'config: ar, split: test' metrics: - name: Wer type: wer value: 44.862730695069324 --- # Whisper Small Ar - Neethu VM 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: 0.3402 - Wer: 44.8627 ## 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 | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.3059 | 0.4156 | 1000 | 0.4141 | 49.8008 | | 0.2894 | 0.8313 | 2000 | 0.3603 | 46.8148 | | 0.1908 | 1.2469 | 3000 | 0.3519 | 46.4806 | | 0.1699 | 1.6625 | 4000 | 0.3402 | 44.8627 | ### Framework versions - Transformers 4.41.1 - Pytorch 2.2.1+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1