--- license: apache-2.0 tags: - generated_from_trainer datasets: - pszemraj/scientific_lay_summarisation-elife-norm metrics: - rouge model-index: - name: long-t5-tglobal-xl-scientific_lay_summarisation-elife-norm-16384-summ-v1 results: - task: name: Summarization type: summarization dataset: name: pszemraj/scientific_lay_summarisation-elife-norm type: pszemraj/scientific_lay_summarisation-elife-norm split: validation metrics: - name: Rouge1 type: rouge value: 47.1446 pipeline_tag: summarization inference: False --- # long-t5-tglobal-xl-sci-simplify-elife This model is a fine-tuned version of [google/long-t5-tglobal-xl](https://huggingface.co/google/long-t5-tglobal-xl) on the pszemraj/scientific_lay_summarisation-elife-norm dataset. It achieves the following results on the evaluation set: - Loss: 1.6666 - Rouge1: 47.1446 - Rouge2: 14.2158 - Rougel: 23.3524 - Rougelsum: 44.6063 - Gen Len: 431.22 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data the `pszemraj/scientific_lay_summarisation-elife-norm` dataset, input 16384 tokens then truncate, output 1024 tokens then truncate. ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 8e-05 - train_batch_size: 1 - eval_batch_size: 1 - seed: 6963 - gradient_accumulation_steps: 8 - total_train_batch_size: 8 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.02 - num_epochs: 2.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| | 1.7959 | 1.0 | 543 | 1.6770 | 44.4187 | 12.6752 | 22.4669 | 41.944 | 456.33 | | 1.7578 | 2.0 | 1086 | 1.6666 | 47.1446 | 14.2158 | 23.3524 | 44.6063 | 431.22 |