--- language: - id license: apache-2.0 base_model: openai/whisper-small 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: train args: id metrics: - name: Wer type: wer value: 0.3947650718729886 --- # Whisper Small Indonesian This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_9_0 id dataset. It achieves the following results on the evaluation set: - Loss: 0.0004 - Wer: 0.3948 ## 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: 12 - eval_batch_size: 6 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.2264 | 2.38 | 1000 | 0.1836 | 14.9989 | | 0.0873 | 4.75 | 2000 | 0.0633 | 5.0869 | | 0.0236 | 7.13 | 3000 | 0.0262 | 1.8086 | | 0.0068 | 9.5 | 4000 | 0.0062 | 0.6222 | | 0.0002 | 11.88 | 5000 | 0.0004 | 0.3948 | ### Framework versions - Transformers 4.31.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.13.1 - Tokenizers 0.13.3