sentiment-pt-pl30-4

apwic/sentiment-pt-pl30-4

sentiment-pt-pl30-4 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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.bin142 MB · 99%

At a glance

License: mit
Access: Public
Created: May 26, 2024
Updated: Jun 3, 2024
SHA: 7c83ae76

Base models

indolem/indobert-base-uncased

Model card

From the Hugging Face model README

sentiment-pt-pl30-4

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: 0.3168
Accuracy: 0.8797
Precision: 0.8530
Recall: 0.8599
F1: 0.8563

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	0.5007	0.7243	0.6593	0.6374	0.6446
0.4584	2.0	244	0.3856	0.8296	0.8123	0.7569	0.7761
0.3559	3.0	366	0.3407	0.8571	0.8638	0.7814	0.8079
0.2961	4.0	488	0.3089	0.8697	0.8438	0.8403	0.8420
0.276	5.0	610	0.2917	0.8622	0.8314	0.8425	0.8365
0.2555	6.0	732	0.2905	0.8697	0.8428	0.8428	0.8428
0.2427	7.0	854	0.3031	0.8772	0.8670	0.8281	0.8440
0.2219	8.0	976	0.2908	0.8772	0.8514	0.8531	0.8522
0.2158	9.0	1098	0.3084	0.8847	0.8760	0.8384	0.8540
0.2	10.0	1220	0.2938	0.8747	0.8457	0.8588	0.8517
0.1885	11.0	1342	0.2977	0.8772	0.8524	0.8506	0.8515
0.183	12.0	1464	0.3070	0.8847	0.8717	0.8434	0.8557
0.1752	13.0	1586	0.2959	0.8797	0.8522	0.8624	0.8570
0.1558	14.0	1708	0.3040	0.8747	0.8447	0.8638	0.8531
0.1538	15.0	1830	0.3082	0.8722	0.8431	0.8546	0.8484
0.152	16.0	1952	0.3100	0.8772	0.8576	0.8406	0.8484
0.1436	17.0	2074	0.3105	0.8747	0.8463	0.8563	0.8510
0.1426	18.0	2196	0.3119	0.8747	0.8471	0.8538	0.8503
0.1398	19.0	2318	0.3164	0.8797	0.8522	0.8624	0.8570
0.14	20.0	2440	0.3168	0.8797	0.8530	0.8599	0.8563

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 26, 2024
Updated: Jun 3, 2024