--- language: - ko license: apache-2.0 tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mangoo111/stt_datasets_mixed base_model: openai/whisper-base model-index: - name: AIHub_non-face-to-face-care_data_model_synthesis results: [] --- # AIHub_non-face-to-face-care_data_model_synthesis This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the AIHub_non-face-to-face-care_data dataset. It achieves the following results on the evaluation set: - Loss: 0.4661 - Cer: 86.6106 - Normalized Cer: 0.1083 ## 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 - lr_scheduler_warmup_steps: 500 - training_steps: 4000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Cer | Normalized Cer | |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------:| | 0.6939 | 2.5 | 1000 | 0.7123 | 100.3264 | 0.1254 | | 0.4626 | 5.0 | 2000 | 0.4787 | 93.8130 | 0.1173 | | 0.3828 | 7.5 | 3000 | 0.4661 | 86.6106 | 0.1083 | | 0.3207 | 10.0 | 4000 | 0.4811 | 99.8114 | 0.1248 | ### Framework versions - Transformers 4.38.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.16.1 - Tokenizers 0.15.1