bdc2024-indobert-filtered-1 – AI Model by Mikask | AlphaNeural AI

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Mikask/
bdc2024-indobert-filtered-1

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text-classification

generated_from_trainer

indobenchmark/indobart

autotrain_compatible

endpoints_compatible

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bdc2024-indobert-filtered-1

This model is a fine-tuned version of indobenchmark/indobart on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5705
Accuracy: 0.8317
Balanced Accuracy: 0.6247
Precision: 0.8316
Recall: 0.8317
F1: 0.8173

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: 1e-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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Balanced Accuracy	Precision	Recall	F1
No log	1.0	298	0.9280	0.6998	0.3859	0.6874	0.6998	0.6350
0.886	2.0	596	0.7598	0.7648	0.4862	0.7263	0.7648	0.7251
0.886	3.0	894	0.6400	0.7992	0.5757	0.8018	0.7992	0.7772
0.5453	4.0	1192	0.5738	0.8298	0.6337	0.8321	0.8298	0.8184
0.5453	5.0	1490	0.5705	0.8317	0.6247	0.8316	0.8317	0.8173

Framework versions

Transformers 4.33.1
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.13.3