bart_summarization_pretrained

This model is a fine-tuned version of facebook/bart-large-cnn on the billsum dataset. It achieves the following results on the evaluation set:

• Loss: 1.7402
• Rouge1: 0.5264
• Rouge2: 0.2745
• Rougel: 0.3432
• Rougelsum: 0.4049
• Gen Len: 131.0645

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: 1
• eval_batch_size: 1
• 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
1.7347	1.0	989	1.6263	0.5044	0.254	0.3219	0.3734	121.8306
1.2029	2.0	1978	1.6037	0.5278	0.2723	0.3351	0.3977	136.4718
0.8435	3.0	2967	1.6054	0.513	0.2661	0.3357	0.3957	129.1048
0.6326	4.0	3956	1.7402	0.5264	0.2745	0.3432	0.4049	131.0645

Framework versions

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