t5-small-billsum-ca

Trisert/t5-small-billsum-ca

t5-small-billsum-ca is a machine learning model from Trisert. 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. --

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At a glance

Library: transformers
License: apache-2.0
Model type: t5
Access: Public
Created: May 26, 2023
Updated: May 26, 2023
SHA: 92b964c9

Model card

From the Hugging Face model README

t5-small-billsum-ca

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.3242
Rouge1: 0.1984
Rouge2: 0.0973
Rougel: 0.1709
Rougelsum: 0.171
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: 4
eval_batch_size: 4
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	248	2.4789	0.15	0.0549	0.1225	0.1225	19.0
No log	2.0	496	2.3740	0.1932	0.092	0.1647	0.165	19.0
2.888	3.0	744	2.3368	0.1982	0.0967	0.1703	0.1704	19.0
2.888	4.0	992	2.3242	0.1984	0.0973	0.1709	0.171	19.0

Framework versions

Transformers 4.30.0.dev0
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3

Library: transformers
Type: t5
License: apache-2.0
Created: May 26, 2023
Updated: May 26, 2023