sentiment-pt-pl20-4

apwic/sentiment-pt-pl20-4

sentiment-pt-pl20-4 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 25, 2024
Updated: Jun 3, 2024
SHA: 24598a15

Base models

indolem/indobert-base-uncased

Model card

From the Hugging Face model README

sentiment-pt-pl20-4

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: 0.3189
Accuracy: 0.8772
Precision: 0.8514
Recall: 0.8531
F1: 0.8522

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
0.55	1.0	122	0.5115	0.7143	0.6535	0.6503	0.6518
0.4708	2.0	244	0.4093	0.8070	0.7770	0.7335	0.7489
0.3841	3.0	366	0.3797	0.8321	0.8611	0.7287	0.7587
0.3154	4.0	488	0.3147	0.8772	0.8670	0.8281	0.8440
0.2764	5.0	610	0.3043	0.8697	0.8488	0.8303	0.8386
0.2589	6.0	732	0.2923	0.8747	0.8537	0.8388	0.8457
0.24	7.0	854	0.3074	0.8647	0.8491	0.8142	0.8286
0.2257	8.0	976	0.3176	0.8596	0.8389	0.8132	0.8243
0.2077	9.0	1098	0.3044	0.8722	0.8562	0.8271	0.8395
0.1982	10.0	1220	0.3065	0.8672	0.8423	0.8335	0.8377
0.1806	11.0	1342	0.2871	0.8822	0.8574	0.8592	0.8583
0.1843	12.0	1464	0.3042	0.8822	0.8596	0.8542	0.8568
0.1792	13.0	1586	0.2948	0.8722	0.8463	0.8446	0.8454
0.1644	14.0	1708	0.2986	0.8797	0.8509	0.8674	0.8583
0.1593	15.0	1830	0.3163	0.8822	0.8535	0.8717	0.8616
0.1517	16.0	1952	0.3026	0.8822	0.8596	0.8542	0.8568
0.1478	17.0	2074	0.3101	0.8822	0.8564	0.8617	0.8590
0.1329	18.0	2196	0.3152	0.8772	0.8504	0.8556	0.8530
0.1363	19.0	2318	0.3179	0.8747	0.8471	0.8538	0.8503
0.1292	20.0	2440	0.3189	0.8772	0.8514	0.8531	0.8522

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 25, 2024
Updated: Jun 3, 2024