xsum_and_billsum_and_samsum

• Loss: 1.8894
• Rouge1: 0.3798
• Rouge2: 0.15
• Rougel: 0.316
• Rougelsum: 0.3158
• Gen Len: 16.1416
• Precision: 0.4394
• Recall: 0.3237
• F1: 0.0
• Hashcode: roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.28.1)-rescaled

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

• learning_rate: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 72
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.28.1
• Pytorch 2.0.0+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3