text-classification – AI Model by dewifaj | AlphaNeural AI

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dewifaj/
text-classification

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text-classification

generated_from_trainer

indolem/indobert-base-uncased

autotrain_compatible

endpoints_compatible

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text-classification

This model is a fine-tuned version of indolem/indobert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.4783
Balanced Accuracy: 0.5328

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Balanced Accuracy
0.2974	1.0	150	1.4783	0.5328
0.2406	2.0	300	1.6163	0.5288
0.3334	3.0	450	1.7306	0.5253
0.2145	4.0	600	1.6787	0.5254
0.1358	5.0	750	1.9275	0.5482
0.081	6.0	900	1.8528	0.5372
0.2184	7.0	1050	1.9453	0.5604
0.0593	8.0	1200	1.9722	0.5558
0.0068	9.0	1350	2.0153	0.5561
0.0531	10.0	1500	2.0004	0.5429

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1