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: 0.5534
Accuracy: 0.8973
Precision: 0.9031
Recall: 0.8973
F1: 0.8997

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.5638	1.0	107	0.4124	0.8527	0.8624	0.8429	0.8504
0.1947	2.0	214	0.4518	0.8938	0.9112	0.8840	0.8933
0.0754	3.0	321	0.5060	0.8904	0.8937	0.8967	0.8950
0.0192	4.0	428	0.5699	0.8973	0.9016	0.8962	0.8981
0.0092	5.0	535	0.5534	0.8973	0.9031	0.8973	0.8997

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

ridho2401/sa-tapera

sa-tapera

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ridho2401/
sa-tapera