summarization-seq_bn-0

apwic/summarization-seq_bn-0

summarization-seq_bn-0 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. --

Downloads · 30 days

Access

Public

Updated Jul 6, 2024

Repo size

106 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin106 MB · 98%

At a glance

License: apache-2.0
Access: Public
Created: Jul 6, 2024
Updated: Jul 6, 2024
SHA: 8a1e9423

Base models

LazarusNLP/IndoNanoT5-base

Model card

From the Hugging Face model README

summarization-seq_bn-0

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: 0.4844
Rouge1: 0.3742
Rouge2: 0.0
Rougel: 0.3702
Rougelsum: 0.3724
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
0.7704	1.0	892	0.5246	0.7067	0.7048	0.7049	1.0
0.6021	2.0	1784	0.5193	0.6627	0.6591	0.6597	1.0
0.5536	3.0	2676	0.4900	0.6414	0.6433	0.641	1.0
0.5164	4.0	3568	0.4899	0.6552	0.6537	0.6541	1.0
0.4856	5.0	4460	0.4844	0.6575	0.6536	0.6567	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