text_shortening_model_v64

ldos/text_shortening_model_v64

text_shortening_model_v64 is a machine learning model from ldos. 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: Sep 29, 2023
Updated: Sep 29, 2023
SHA: e483d40f

Base models

Model card

From the Hugging Face model README

text_shortening_model_v64

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

Loss: 2.3622
Bert precision: 0.7381
Bert recall: 0.7763
Bert f1-score: 0.7541
Average word count: 9.0345
Max word count: 14
Min word count: 2
Average token count: 15.5862
% shortened texts with length > 12: 20.6897

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: 0.0001
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: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Bert precision	Bert recall	Bert f1-score	Average word count	Max word count	Min word count	Average token count	% shortened texts with length > 12
3.1461	1.0	5	2.3622	0.7381	0.7763	0.7541	9.0345	14	2	15.5862	20.6897

Framework versions

Transformers 4.33.1
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3

Library: transformers
Type: t5
License: apache-2.0
Created: Sep 29, 2023
Updated: Sep 29, 2023