indobert-QA-multiple-choice-fine-tune-IndoCareer – AI Model by FaishalbhiteX | AlphaNeural AI

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FaishalbhiteX/
indobert-QA-multiple-choice-fine-tune-IndoCareer

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multiple-choice

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indolem/indobert-base-uncased

endpoints_compatible

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indobert-QA-multiple-choice-fine-tune-IndoCareer

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: 2.4538
Accuracy: 0.2588
F1: 0.1064

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: 3e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	220	2.6991	0.2588	0.1064
No log	2.0	440	2.5215	0.2109	0.1074
3.1493	3.0	660	2.4573	0.2588	0.1064
3.1493	4.0	880	2.4262	0.2588	0.1064
2.4278	4.9795	1095	2.4538	0.2588	0.1064

Framework versions

Transformers 4.49.0
Pytorch 2.5.1+cu124
Datasets 3.3.2
Tokenizers 0.21.0