--- license: apache-2.0 base_model: RMWeerasinghe/long-t5-tglobal-base-finetuned-govReport-4096 tags: - summarization - generated_from_trainer metrics: - rouge model-index: - name: long-t5-tglobal-base-boardpapers-4096 results: [] --- # long-t5-tglobal-base-boardpapers-4096 This model is a fine-tuned version of [RMWeerasinghe/long-t5-tglobal-base-finetuned-govReport-4096](https://huggingface.co/RMWeerasinghe/long-t5-tglobal-base-finetuned-govReport-4096) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5617 - Rouge1: 0.0743 - Rouge2: 0.0398 - Rougel: 0.0589 - Rougelsum: 0.0703 ## 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: 4e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| | No log | 0.67 | 1 | 0.6654 | 0.0514 | 0.0197 | 0.0386 | 0.0477 | | No log | 2.0 | 3 | 0.6378 | 0.0667 | 0.0309 | 0.0512 | 0.0596 | | No log | 2.67 | 4 | 0.6293 | 0.0646 | 0.0274 | 0.0515 | 0.0619 | | No log | 4.0 | 6 | 0.6128 | 0.0706 | 0.0377 | 0.0566 | 0.067 | | No log | 4.67 | 7 | 0.6049 | 0.0706 | 0.0377 | 0.0566 | 0.067 | | No log | 6.0 | 9 | 0.5935 | 0.0706 | 0.0377 | 0.0566 | 0.067 | | No log | 6.67 | 10 | 0.5891 | 0.0718 | 0.0385 | 0.0578 | 0.067 | | No log | 8.0 | 12 | 0.5815 | 0.0743 | 0.0398 | 0.0589 | 0.0703 | | No log | 8.67 | 13 | 0.5785 | 0.0743 | 0.0398 | 0.0589 | 0.0703 | | No log | 10.0 | 15 | 0.5742 | 0.0743 | 0.0398 | 0.0589 | 0.0703 | | No log | 10.67 | 16 | 0.5724 | 0.0743 | 0.0398 | 0.0589 | 0.0703 | | No log | 12.0 | 18 | 0.5694 | 0.0743 | 0.0398 | 0.0589 | 0.0703 | | No log | 12.67 | 19 | 0.5681 | 0.0743 | 0.0398 | 0.0589 | 0.0703 | | 0.7929 | 14.0 | 21 | 0.5661 | 0.0743 | 0.0398 | 0.0589 | 0.0703 | | 0.7929 | 14.67 | 22 | 0.5652 | 0.0743 | 0.0398 | 0.0589 | 0.0703 | | 0.7929 | 16.0 | 24 | 0.5636 | 0.0743 | 0.0398 | 0.0589 | 0.0703 | | 0.7929 | 16.67 | 25 | 0.5630 | 0.0743 | 0.0398 | 0.0589 | 0.0703 | | 0.7929 | 18.0 | 27 | 0.5621 | 0.0743 | 0.0398 | 0.0589 | 0.0703 | | 0.7929 | 18.67 | 28 | 0.5619 | 0.0743 | 0.0398 | 0.0589 | 0.0703 | | 0.7929 | 20.0 | 30 | 0.5617 | 0.0743 | 0.0398 | 0.0589 | 0.0703 | ### Framework versions - Transformers 4.37.0 - Pytorch 2.1.2 - Datasets 2.17.0 - Tokenizers 0.15.1