--- language: - ko license: apache-2.0 base_model: openai/whisper-base tags: - hf-asr-leaderboard - generated_from_trainer datasets: - potatoSeop/chimsuja_dataset model-index: - name: whisper-chimsuja results: [] --- # whisper-chimsuja This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the potatoSeop/chimsuja_dataset dataset. It achieves the following results on the evaluation set: - Loss: 0.3795 - Cer: 12.0513 ## 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: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Cer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.913 | 0.4 | 50 | 0.4665 | 14.4249 | | 0.4203 | 0.79 | 100 | 0.4156 | 18.1852 | | 0.343 | 1.19 | 150 | 0.3972 | 13.9544 | | 0.2746 | 1.59 | 200 | 0.3891 | 13.2048 | | 0.2838 | 1.98 | 250 | 0.3827 | 13.8794 | | 0.2153 | 2.38 | 300 | 0.3808 | 12.0721 | | 0.2035 | 2.78 | 350 | 0.3795 | 12.0513 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu121 - Datasets 2.16.0 - Tokenizers 0.15.0