--- language: - ar license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - Arbi-Houssem/Tunisian_dataset_STT-TTS1 metrics: - wer model-index: - name: Whisper Tunisien results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Tunisian_dataset_STT-TTS1 type: Arbi-Houssem/Tunisian_dataset_STT-TTS1 args: 'config: ar, split: test' metrics: - name: Wer type: wer value: 102.98313878080414 --- # Whisper Tunisien This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Tunisian_dataset_STT-TTS1 dataset. It achieves the following results on the evaluation set: - Loss: 2.8010 - Wer: 102.9831 ## 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-07 - train_batch_size: 8 - eval_batch_size: 16 - 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 | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 1.1413 | 10.3093 | 1000 | 2.9765 | 135.4086 | | 1.0017 | 20.6186 | 2000 | 2.8593 | 107.4578 | | 0.9227 | 30.9278 | 3000 | 2.8201 | 100.3891 | | 0.8583 | 41.2371 | 4000 | 2.8054 | 102.9831 | | 0.8442 | 51.5464 | 5000 | 2.8010 | 102.9831 | ### Framework versions - Transformers 4.42.0.dev0 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1