metadata

license: mit
base_model: ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: best_berita_bert_model_fold_5
    results: []

best_berita_bert_model_fold_5

This model is a fine-tuned version of ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0859
Accuracy: 0.9833
Precision: 0.9834
Recall: 0.9830
F1: 0.9832

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.5542	1.0	601	0.3531	0.9142	0.9204	0.9129	0.9108
0.266	2.0	1202	0.1554	0.9625	0.9634	0.9620	0.9618
0.1215	3.0	1803	0.0859	0.9833	0.9834	0.9830	0.9832
0.0721	4.0	2404	0.1634	0.9725	0.9736	0.9721	0.9720
0.0227	5.0	3005	0.4132	0.9484	0.9527	0.9475	0.9470
0.0242	6.0	3606	0.2816	0.9609	0.9632	0.9602	0.9599
0.0083	7.0	4207	0.2295	0.9717	0.9731	0.9712	0.9712
0.0	8.0	4808	0.1644	0.9792	0.9800	0.9788	0.9789
0.0002	9.0	5409	0.1868	0.9784	0.9792	0.9780	0.9781
0.0	10.0	6010	0.1901	0.9784	0.9792	0.9780	0.9781

Framework versions

Transformers 4.42.3
Pytorch 2.1.2
Datasets 2.20.0
Tokenizers 0.19.1