billsum-model-2 – AI Model by cs608 | AlphaNeural AI

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billsum-model-2

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text2text-generation

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CS685-text-summarizer-2

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

Loss: 1.7516
Rouge1: 17.4066
Rouge2: 14.022
Rougel: 16.9378
Rougelsum: 17.0519

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: 5.6e-05
train_batch_size: 6
eval_batch_size: 6
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
2.3529	1.0	1052	1.9277	17.1288	13.5932	16.6346	16.7728
1.9686	2.0	2104	1.8297	17.2756	13.7685	16.7924	16.9242
1.789	3.0	3156	1.7903	17.4219	14.0205	16.9082	17.0564
1.6619	4.0	4208	1.7632	17.5055	14.1186	16.996	17.1265
1.5819	5.0	5260	1.7516	17.4066	14.022	16.9378	17.0519

Framework versions

Transformers 4.28.0
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3