--- library_name: transformers language: - ko license: apache-2.0 base_model: morish/whisper-medium-ko-v0_1_1 tags: - morish/kresp_speech_87_48278_150000 - morish/open_communication_109_48652_150000 - morish/senior_kspeech_107_150000 - morish/telemedicine_208_150000_200000 - morish/welfare_470_150000_200000 - whisper-2024-09-06 - generated_from_trainer model-index: - name: whisper-ko-finetune results: [] --- # whisper-ko-finetune This model is a fine-tuned version of [morish/whisper-medium-ko-v0_1_1](https://huggingface.co/morish/whisper-medium-ko-v0_1_1) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0829 - Cer: 2.4784 ## 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-06 - train_batch_size: 32 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.01 - num_epochs: 1 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Cer | |:-------------:|:------:|:----:|:---------------:|:------:| | 0.0868 | 0.2385 | 500 | 0.0859 | 2.5607 | | 0.0856 | 0.4770 | 1000 | 0.0843 | 2.5300 | | 0.0875 | 0.7155 | 1500 | 0.0833 | 2.4804 | | 0.0815 | 0.9540 | 2000 | 0.0829 | 2.4784 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1