indosum-seq_bn-rf64-0

apwic/indosum-seq_bn-rf64-0

indosum-seq_bn-rf64-0 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 22, 2024

Repo size

101 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin101 MB · 96%

At a glance

License: apache-2.0
Access: Public
Created: Jul 22, 2024
Updated: Jul 22, 2024
SHA: ede44559

Base models

LazarusNLP/IndoNanoT5-base

Model card

From the Hugging Face model README

indosum-seq_bn-rf64-0

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: 0.5046
Rouge1: 72.7451
Rouge2: 65.6426
Rougel: 69.7965
Rougelsum: 71.8443
Gen Len: 103.1187

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	Rouge2	Rougel	Rougelsum	Gen Len
0.8386	1.0	892	0.5658	68.0586	60.6185	65.0879	67.0846	102.556
0.646	2.0	1784	0.5346	69.6096	62.3885	66.6327	68.7343	107.088
0.6031	3.0	2676	0.5019	70.498	63.0668	67.3204	69.5075	101.6693
0.5753	4.0	3568	0.5093	71.6759	64.4776	68.7095	70.7692	104.52
0.5551	5.0	4460	0.5046	72.0617	64.9137	69.0991	71.1205	102.5733

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 22, 2024
Updated: Jul 22, 2024