This model is a fine-tuned version of indolem/indobertweet-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4131
Accuracy: 0.925
Precision: 0.9320
Recall: 0.9231
F1: 0.9271

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: 0.0001
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.4966	1.0	169	0.2953	0.9017	0.9150	0.8870	0.8987
0.1633	2.0	338	0.2859	0.92	0.9322	0.9151	0.9226
0.0495	3.0	507	0.3495	0.9317	0.9349	0.9289	0.9317
0.013	4.0	676	0.4131	0.925	0.9320	0.9231	0.9271

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

bwahyuh/gemashsentiment

gemashsentiment

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

bwahyuh/
gemashsentiment