--- license: mit tags: - generated_from_trainer metrics: - rouge model-index: - name: kobart_32_6e-5_datav2_min30_lp5.0_temperature1.0 results: [] --- # kobart_32_6e-5_datav2_min30_lp5.0_temperature1.0 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: 2.6110 - Rouge1: 35.8879 - Rouge2: 12.9302 - Rougel: 23.7819 - Bleu1: 30.0048 - Bleu2: 17.5297 - Bleu3: 10.3153 - Bleu4: 5.9092 - Gen Len: 50.8508 ## 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: 6e-05 - train_batch_size: 32 - eval_batch_size: 128 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 5.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Bleu1 | Bleu2 | Bleu3 | Bleu4 | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:------:|:-------:| | 1.5664 | 3.78 | 5000 | 2.6110 | 35.8879 | 12.9302 | 23.7819 | 30.0048 | 17.5297 | 10.3153 | 5.9092 | 50.8508 | ### Framework versions - Transformers 4.25.1 - Pytorch 1.13.0+cu117 - Datasets 2.7.1 - Tokenizers 0.13.2