--- tags: - generated_from_trainer datasets: - reddit metrics: - rouge model-index: - name: pegasus-reddit results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: reddit type: reddit args: default metrics: - name: Rouge1 type: rouge value: 23.967 --- # pegasus-reddit This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the reddit dataset. It achieves the following results on the evaluation set: - Loss: 3.3329 - Rouge1: 23.967 - Rouge2: 5.0032 - Rougel: 15.3267 - Rougelsum: 18.5905 - Gen Len: 69.2193 ## 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: 6.35e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 500 - num_epochs: 1.0 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.16.2 - Pytorch 1.10.1 - Datasets 1.17.0 - Tokenizers 0.10.3