sentiment-pt-pl30-1

apwic/sentiment-pt-pl30-1

sentiment-pt-pl30-1 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 mit.

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

Downloads · 30 days

Access

Public

Updated Jun 3, 2024

Repo size

185 MB

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Public

Hugging Face

Repo makeup

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At a glance

License: mit
Access: Public
Created: May 19, 2024
Updated: Jun 3, 2024
SHA: ff150801

Base models

indolem/indobert-base-uncased

Model card

From the Hugging Face model README

sentiment-pt-pl30-1

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

Loss: 0.3019
Accuracy: 0.8647
Precision: 0.8377
Recall: 0.8342
F1: 0.8359

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: 30
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.5413	1.0	122	0.4949	0.7368	0.6763	0.6438	0.6531
0.4306	2.0	244	0.3954	0.8246	0.7902	0.8259	0.8019
0.3344	3.0	366	0.3397	0.8521	0.8370	0.7929	0.8099
0.2925	4.0	488	0.3211	0.8471	0.8264	0.7918	0.8058
0.2794	5.0	610	0.3064	0.8622	0.8314	0.8425	0.8365
0.2464	6.0	732	0.2857	0.8672	0.8356	0.8585	0.8453
0.2332	7.0	854	0.2846	0.8772	0.8496	0.8581	0.8537
0.2216	8.0	976	0.2906	0.8596	0.8360	0.8182	0.8262
0.2123	9.0	1098	0.2781	0.8697	0.8488	0.8303	0.8386
0.1911	10.0	1220	0.2896	0.8722	0.8562	0.8271	0.8395
0.1878	11.0	1342	0.2814	0.8747	0.8479	0.8513	0.8496
0.1797	12.0	1464	0.2830	0.8672	0.8402	0.8385	0.8394
0.1746	13.0	1586	0.2900	0.8672	0.8496	0.8210	0.8332
0.1677	14.0	1708	0.2798	0.8697	0.8411	0.8478	0.8443
0.1585	15.0	1830	0.2823	0.8722	0.8437	0.8521	0.8477
0.1575	16.0	1952	0.2816	0.8722	0.8413	0.8646	0.8511
0.146	17.0	2074	0.3027	0.8647	0.8377	0.8342	0.8359
0.1368	18.0	2196	0.2961	0.8672	0.8372	0.8485	0.8425
0.133	19.0	2318	0.3024	0.8622	0.8342	0.8325	0.8333
0.1377	20.0	2440	0.3019	0.8647	0.8377	0.8342	0.8359

Framework versions

Transformers 4.39.3
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.15.2

License: mit
Languages: id
Created: May 19, 2024
Updated: Jun 3, 2024