--- 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: 43.84929641398094 --- # 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: 0.8616 - Wer: 43.8493 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.9631 | 0.41 | 1000 | 1.3609 | 83.4771 | | 0.7929 | 0.81 | 2000 | 1.1653 | 89.6440 | | 0.4189 | 1.22 | 3000 | 1.0419 | 61.6497 | | 0.3195 | 1.62 | 4000 | 0.9384 | 45.4380 | | 0.1179 | 2.03 | 5000 | 0.8616 | 43.8493 | ### Framework versions - Transformers 4.31.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.13.1 - Tokenizers 0.13.3