--- license: mit base_model: gogamza/kobart-base-v2 tags: - generated_from_trainer metrics: - bleu model-index: - name: Gyeongsang_encoder results: [] --- # Gyeongsang_encoder This model is a fine-tuned version of [gogamza/kobart-base-v2](https://huggingface.co/gogamza/kobart-base-v2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0062 - Bleu: 91.4436 - Gen Len: 13.3478 ## 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: 2e-05 - train_batch_size: 32 - eval_batch_size: 32 - 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 | Bleu | Gen Len | |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:| | 0.0054 | 1.0 | 12910 | 0.0072 | 91.1948 | 13.3484 | | 0.0052 | 2.0 | 25820 | 0.0063 | 91.3684 | 13.3464 | | 0.0043 | 3.0 | 38730 | 0.0062 | 91.4436 | 13.3478 | ### Framework versions - Transformers 4.42.0.dev0 - Pytorch 2.2.1+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1