--- tags: - generated_from_trainer datasets: - xsum metrics: - rouge model-index: - name: large-3-3 results: - task: name: Summarization type: summarization dataset: name: xsum type: xsum config: default split: validation args: default metrics: - name: Rouge1 type: rouge value: 38.9375 --- # large-3-3 This model is a fine-tuned version of [x/large-3-3/](https://huggingface.co/x/large-3-3/) on the xsum dataset. It achieves the following results on the evaluation set: - Loss: 1.7469 - Rouge1: 38.9375 - Rouge2: 15.8853 - Rougel: 31.2177 - Rougelsum: 31.2093 - Gen Len: 26.5882 ## 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: 0.0001 - train_batch_size: 16 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant - num_epochs: 3.0 ### Training results ### Framework versions - Transformers 4.27.0.dev0 - Pytorch 1.13.1+cu117 - Datasets 2.10.0 - Tokenizers 0.13.2