--- 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: 23.40004600874166 --- # 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: 0.3697 - Wer: 23.4000 ## 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: 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.5013 | 0.48 | 1000 | 0.4523 | 28.5990 | | 0.4145 | 0.97 | 2000 | 0.4067 | 25.8109 | | 0.2437 | 1.45 | 3000 | 0.3821 | 24.3800 | | 0.2566 | 1.94 | 4000 | 0.3695 | 23.9798 | | 0.1161 | 2.42 | 5000 | 0.3697 | 23.4000 | ### Framework versions - Transformers 4.31.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.13.1 - Tokenizers 0.13.3