--- 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: 38.89501329356072 --- # 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: 0.7352 - Wer: 38.8950 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.296 | 0.13 | 1000 | 1.3286 | 110.0123 | | 1.1522 | 0.26 | 2000 | 1.0917 | 81.6354 | | 1.0175 | 0.39 | 3000 | 0.9399 | 60.1258 | | 0.7844 | 0.52 | 4000 | 0.8174 | 43.4862 | | 0.5919 | 0.64 | 5000 | 0.7352 | 38.8950 | ### Framework versions - Transformers 4.31.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.13.1 - Tokenizers 0.13.3