--- license: apache-2.0 base_model: Danish-summarisation/DanSumT5-large tags: - generated_from_trainer metrics: - rouge model-index: - name: DanSumT5-large-finetuned-test_57626 results: [] --- # DanSumT5-large-finetuned-test_57626 This model is a fine-tuned version of [Danish-summarisation/DanSumT5-large](https://huggingface.co/Danish-summarisation/DanSumT5-large) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.5370 - Rouge1: 31.992 - Rouge2: 7.6605 - Rougel: 18.1676 - Rougelsum: 29.1825 - Gen Len: 126.27 ## 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: 1 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:| | No log | 1.0 | 200 | 2.5665 | 31.8442 | 7.5263 | 18.0111 | 29.1725 | 126.86 | | No log | 2.0 | 400 | 2.5370 | 31.992 | 7.6605 | 18.1676 | 29.1825 | 126.27 | ### Framework versions - Transformers 4.32.1 - Pytorch 2.1.0 - Datasets 2.12.0 - Tokenizers 0.13.3