--- license: apache-2.0 base_model: openai/whisper-small tags: - whisper-event - generated_from_trainer datasets: - yt metrics: - wer model-index: - name: Whisper Small Indonesian results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: yt id type: yt metrics: - name: Wer type: wer value: 59.84047727125349 --- # Whisper Small Indonesian This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the yt id dataset. It achieves the following results on the evaluation set: - Loss: 0.9773 - Wer: 59.8405 ## 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: 0.0001 - train_batch_size: 4 - eval_batch_size: 2 - 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 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 2.2491 | 0.09 | 1000 | 1.9142 | 226.4834 | | 1.4702 | 0.17 | 2000 | 1.6154 | 115.5502 | | 1.609 | 0.26 | 3000 | 1.3599 | 113.3454 | | 1.1817 | 0.34 | 4000 | 1.1253 | 68.4067 | | 0.9678 | 0.43 | 5000 | 0.9773 | 59.8405 | ### Framework versions - Transformers 4.31.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.13.1 - Tokenizers 0.13.3