summarization-seq_bn-2

apwic/summarization-seq_bn-2

summarization-seq_bn-2 is a machine learning model from apwic. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.

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

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Public

Updated Jul 6, 2024

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106 MB

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Hugging Face

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At a glance

License: apache-2.0
Access: Public
Created: Jul 6, 2024
Updated: Jul 6, 2024
SHA: 12a7563a

Base models

LazarusNLP/IndoNanoT5-base

Model card

From the Hugging Face model README

summarization-seq_bn-2

This model is a fine-tuned version of LazarusNLP/IndoNanoT5-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4666
Rouge1: 0.4096
Rouge2: 0.0
Rougel: 0.4093
Rougelsum: 0.4102
Gen Len: 1.0

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: 0.001
train_batch_size: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rougel	Rougelsum	Gen Len
0.781	1.0	894	0.5142	0.6277	0.6309	0.628	1.0
0.6103	2.0	1788	0.4834	0.6516	0.6528	0.6502	1.0
0.5612	3.0	2682	0.4769	0.6537	0.654	0.6571	1.0
0.5242	4.0	3576	0.4704	0.6285	0.6294	0.6312	1.0
0.4933	5.0	4470	0.4666	0.6446	0.6437	0.6455	1.0

Framework versions

Transformers 4.40.2
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

License: apache-2.0
Languages: id
Created: Jul 6, 2024
Updated: Jul 6, 2024