text-summarization

wjudy/text-summarization

text-summarization is a machine learning model from wjudy. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

4% of all-time downloads

All-time downloads

322

Public

Repo size

484 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin242 MB · 99%

At a glance

Library: transformers
License: apache-2.0
Model type: t5
Access: Public
Created: Mar 19, 2023
Updated: Mar 22, 2023
SHA: db67fdc6

Datasets

billsum

Model card

From the Hugging Face model README

text-summarization

This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:

Loss: 2.5397
Rouge1: 0.1306
Rouge2: 0.0442
Rougel: 0.1096
Rougelsum: 0.1093
Gen Len: 19.0

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	62	2.8278	0.1276	0.0368	0.1083	0.1078	19.0
No log	2.0	124	2.6203	0.1333	0.0459	0.1127	0.1125	19.0
No log	3.0	186	2.5566	0.1292	0.0434	0.1075	0.1074	19.0
No log	4.0	248	2.5397	0.1306	0.0442	0.1096	0.1093	19.0

Framework versions

Transformers 4.27.2
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2

Library: transformers
Type: t5
License: apache-2.0
Created: Mar 19, 2023
Updated: Mar 22, 2023