prophetnet_summarization_pretrained

This model is a fine-tuned version of microsoft/prophetnet-large-uncased on the billsum dataset. It achieves the following results on the evaluation set:

• Loss: 2.3683
• Rouge1: 0.4982
• Rouge2: 0.2267
• Rougel: 0.2983
• Rougelsum: 0.2985
• Gen Len: 139.3831

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: 2e-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: linear
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	124	2.5178	0.4894	0.2223	0.2903	0.2903	139.8105
No log	2.0	248	2.4170	0.4973	0.2279	0.2975	0.297	140.6492
No log	3.0	372	2.3895	0.4964	0.2282	0.2984	0.2981	138.5323
No log	4.0	496	2.3683	0.4982	0.2267	0.2983	0.2985	139.3831

Framework versions

• Transformers 4.29.2
• Pytorch 2.0.1+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3