bdc2024-indobart-gpt-aug – AI Model by andrianangg | AlphaNeural AI

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andrianangg/
bdc2024-indobart-gpt-aug

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text-classification

generated_from_trainer

indobenchmark/indobart

autotrain_compatible

endpoints_compatible

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bdc2024-indobart-gpt-aug

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

Loss: 0.4480
Accuracy: 0.9273
Balanced Accuracy: 0.8560
Precision: 0.9296
Recall: 0.9273
F1: 0.9205

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: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Balanced Accuracy	Precision	Recall	F1
No log	1.0	483	0.7053	0.7820	0.5122	0.7407	0.7820	0.7499
0.8051	2.0	966	0.5075	0.8757	0.6954	0.8779	0.8757	0.8622
0.4597	3.0	1449	0.4041	0.9197	0.8361	0.9198	0.9197	0.9122
0.2475	4.0	1932	0.4224	0.9254	0.8626	0.9255	0.9254	0.9202
0.1303	5.0	2415	0.4438	0.9273	0.8559	0.9295	0.9273	0.9214
0.0771	6.0	2898	0.4480	0.9273	0.8560	0.9296	0.9273	0.9205

Framework versions

Transformers 4.33.1
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.13.3