--- language: - id license: apache-2.0 base_model: openai/whisper-base tags: - whisper-event - generated_from_trainer datasets: - mozilla-foundation/common_voice_9_0 metrics: - wer model-index: - name: Whisper Small Indonesian results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_9_0 id type: mozilla-foundation/common_voice_9_0 config: id split: test args: id metrics: - name: Wer type: wer value: 23.19300667126754 --- # Whisper Small Indonesian This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_9_0 id dataset. It achieves the following results on the evaluation set: - Loss: 0.3793 - Wer: 23.1930 ## 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: 8 - eval_batch_size: 4 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.4648 | 0.97 | 1000 | 0.4258 | 27.6236 | | 0.2992 | 1.94 | 2000 | 0.3831 | 24.4444 | | 0.1597 | 2.9 | 3000 | 0.3778 | 23.6163 | | 0.1137 | 3.87 | 4000 | 0.3793 | 23.1930 | | 0.0632 | 4.84 | 5000 | 0.3893 | 23.5013 | ### Framework versions - Transformers 4.31.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.13.1 - Tokenizers 0.13.3