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YagiASAFAS/
malaysia-news-classification-bert-english-skewness-fixed

Name: malaysia-news-classification-bert-english-skewness-fixed
Availability: InStock

generated_from_trainer

apache-2.0

autotrain_compatible

endpoints_compatible

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malaysia-news-classification-bert-english-skewness-fixed

This model is a fine-tuned version of bert-base-uncased on tnwei/ms-newspapers dataset. It is a fixed version of YagiASAFAS/malaysia-news-classification-bert-english, which fixed the skewness of imbalanced distribution among categories. It achieves the following results on the evaluation set:

Loss: 1.2051
Accuracy: 0.8436

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: 8
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 16
mixed_precision_training: Native AMP

Label Mappings

This model can predict the following labels:

0: Election
1: Political Issue
2: Corruption
3: Democracy
4: Economic Growth
5: Economic Disparity
6: Economic Subsidy
7: Ethnic Discrimination
8: Ethnic Relation
9: Ethnic Culture
10: Religious Issue
11: Business and Finance
12: Sport
13: Food
14: Entertainment
15: Environmental Issue
16: Domestic News
17: World News

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	358	0.9357	0.7486
1.3554	2.0	716	0.9041	0.7807
0.4851	3.0	1074	0.7842	0.8282
0.4851	4.0	1432	0.9478	0.8226
0.2558	5.0	1790	1.0765	0.8282
0.1084	6.0	2148	1.1310	0.8380
0.0625	7.0	2506	1.0999	0.8464
0.0625	8.0	2864	1.1391	0.8408
0.0301	9.0	3222	1.1036	0.8506
0.0171	10.0	3580	1.0765	0.8534
0.0171	11.0	3938	1.1291	0.8506
0.0129	12.0	4296	1.1360	0.8520
0.0035	13.0	4654	1.1619	0.8450
0.0039	14.0	5012	1.1727	0.8534
0.0039	15.0	5370	1.2079	0.8408
0.0031	16.0	5728	1.2051	0.8436

Framework versions

Transformers 4.18.0
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.12.1

YagiASAFAS/malaysia-news-classification-bert-english-skewness-fixed

malaysia-news-classification-bert-english-skewness-fixed

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Label Mappings

Training results

Framework versions

YagiASAFAS/
malaysia-news-classification-bert-english-skewness-fixed