dialogsum

Kekega/dialogsum

dialogsum is a machine learning model from Kekega. 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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Hugging Face

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At a glance

Library: transformers
License: apache-2.0
Model type: t5
Access: Public
Created: Dec 18, 2023
Updated: Dec 18, 2023
SHA: 8a8fae0c

Base models

google/flan-t5-base

Model card

From the Hugging Face model README

dialogsum

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

Loss: 1.0245
Rouge1: 45.6581
Rouge2: 15.9871
Rougel: 43.5188
Rougelsum: 43.913
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: 5e-05
train_batch_size: 8
eval_batch_size: 8
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	Gen Len
1.2634	1.0	786	1.1040	42.2483	13.4135	40.3622	40.5436	19.0
1.1931	2.0	1572	1.0637	41.6604	14.0866	39.7604	39.9971	19.0
1.1347	3.0	2358	1.0421	45.0247	14.5438	42.8164	43.1956	19.0
1.1155	4.0	3144	1.0312	45.6977	16.2231	43.5457	43.8965	19.0
1.0827	5.0	3930	1.0245	45.6581	15.9871	43.5188	43.913	19.0

Framework versions

Transformers 4.35.2
Pytorch 2.0.1+cu117
Datasets 2.15.0
Tokenizers 0.15.0

Library: transformers
Type: t5
License: apache-2.0
Created: Dec 18, 2023
Updated: Dec 18, 2023