metadata

language:
  - id
license: mit
base_model: indolem/indobert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: sentiment-base-0
    results: []

sentiment-base-0

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: 0.3540
Accuracy: 0.8546
Precision: 0.8233
Recall: 0.8297
F1: 0.8264

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: 30
eval_batch_size: 8
seed: 1
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.5623	1.0	122	0.5053	0.7168	0.6410	0.5796	0.5795
0.518	2.0	244	0.4861	0.7293	0.6674	0.5960	0.5998
0.4835	3.0	366	0.4552	0.7694	0.7211	0.7094	0.7145
0.4497	4.0	488	0.4223	0.7945	0.7521	0.7521	0.7521
0.4266	5.0	610	0.3996	0.8170	0.7814	0.7680	0.7741
0.3907	6.0	732	0.3830	0.8195	0.7818	0.7873	0.7845
0.3742	7.0	854	0.3684	0.8346	0.8016	0.7955	0.7984
0.3616	8.0	976	0.3720	0.8271	0.7902	0.8051	0.7968
0.3294	9.0	1098	0.3689	0.8371	0.8019	0.8147	0.8077
0.3207	10.0	1220	0.3632	0.8396	0.8047	0.8190	0.8111
0.3214	11.0	1342	0.3577	0.8371	0.8017	0.8172	0.8086
0.3167	12.0	1464	0.3607	0.8396	0.8046	0.8215	0.8119
0.289	13.0	1586	0.3684	0.8346	0.7988	0.8155	0.8061
0.2997	14.0	1708	0.3480	0.8496	0.8193	0.8161	0.8177
0.2986	15.0	1830	0.3576	0.8496	0.8169	0.8261	0.8212
0.2914	16.0	1952	0.3497	0.8496	0.8180	0.8211	0.8195
0.278	17.0	2074	0.3540	0.8521	0.8207	0.8254	0.8229
0.2887	18.0	2196	0.3516	0.8521	0.8207	0.8254	0.8229
0.2829	19.0	2318	0.3537	0.8521	0.8207	0.8254	0.8229
0.2771	20.0	2440	0.3540	0.8546	0.8233	0.8297	0.8264

Framework versions

Transformers 4.39.3
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.15.2