results_indobert_emotion – AI Model by Alfanatasya | AlphaNeural AI

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Alfanatasya/
results_indobert_emotion

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text-classification

generated_from_trainer

indobenchmark/indobert-large-p1

autotrain_compatible

endpoints_compatible

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results_indobert_emotion

This model is a fine-tuned version of indobenchmark/indobert-large-p1 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7407
Accuracy: 0.7682
Precision: 0.7698
Recall: 0.7773
F1: 0.7668

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: 32
eval_batch_size: 32
seed: 42
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_steps: 500
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.6564	1.0	111	1.5223	0.2955	0.3507	0.2474	0.1849
1.3092	2.0	222	1.0048	0.6205	0.6162	0.6264	0.6064
0.8835	3.0	333	0.7088	0.75	0.7506	0.7557	0.7491
0.6384	4.0	444	0.7077	0.7477	0.7458	0.7658	0.7499
0.4962	5.0	555	0.7407	0.7682	0.7698	0.7773	0.7668
0.3875	6.0	666	0.7610	0.7477	0.7457	0.7649	0.7517
0.2849	7.0	777	0.8377	0.7523	0.7565	0.7598	0.7545

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1