--- license: apache-2.0 base_model: openai/whisper-tiny tags: - whisper-event - generated_from_trainer datasets: - nadsoft/QASR-Speech-Resource metrics: - wer model-index: - name: Whisper Small Arabic results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: nadsoft/QASR-Speech-Resource default type: nadsoft/QASR-Speech-Resource metrics: - name: Wer type: wer value: 42.76086285863452 --- # Whisper Small Arabic This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the nadsoft/QASR-Speech-Resource default dataset. It achieves the following results on the evaluation set: - Loss: 0.5583 - Wer: 42.7609 ## 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: 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: 10000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:-----:|:---------------:|:-------:| | 0.7005 | 0.2 | 2000 | 0.7135 | 51.5366 | | 0.6267 | 0.4 | 4000 | 0.6309 | 50.9433 | | 0.5886 | 0.6 | 6000 | 0.5892 | 50.0225 | | 0.5627 | 0.8 | 8000 | 0.5679 | 43.9450 | | 0.5694 | 1.0 | 10000 | 0.5583 | 42.7609 | ### Framework versions - Transformers 4.38.0.dev0 - Pytorch 2.1.0+cu121 - Datasets 2.17.1.dev0 - Tokenizers 0.15.1