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-2
    results: []

sentiment-base-2

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: 0.8886
Accuracy: 0.8922
Precision: 0.8719
Recall: 0.8662
F1: 0.8690

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: 42
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
0.3808	1.0	122	0.3794	0.8647	0.8737	0.7917	0.8186
0.221	2.0	244	0.2851	0.8722	0.8562	0.8271	0.8395
0.1363	3.0	366	0.3832	0.8947	0.8757	0.8680	0.8717
0.099	4.0	488	0.4968	0.8972	0.8869	0.8598	0.8717
0.0702	5.0	610	0.5205	0.8697	0.8503	0.8278	0.8377
0.0469	6.0	732	0.5740	0.8747	0.8552	0.8363	0.8448
0.0328	7.0	854	0.6012	0.8847	0.8581	0.8684	0.8629
0.0284	8.0	976	0.5403	0.8972	0.8812	0.8673	0.8738
0.019	9.0	1098	0.5909	0.8922	0.8657	0.8813	0.8728
0.016	10.0	1220	0.8931	0.8822	0.8694	0.8392	0.8521
0.0167	11.0	1342	0.6618	0.8972	0.8781	0.8723	0.8751
0.0168	12.0	1464	0.7513	0.9023	0.8842	0.8783	0.8812
0.0064	13.0	1586	0.7513	0.8997	0.8819	0.8741	0.8778
0.0078	14.0	1708	0.8152	0.8947	0.8789	0.8630	0.8704
0.0064	15.0	1830	0.7460	0.8997	0.8778	0.8816	0.8797
0.0055	16.0	1952	0.8232	0.8922	0.8734	0.8637	0.8683
0.006	17.0	2074	0.8421	0.8947	0.8757	0.8680	0.8717
0.0052	18.0	2196	0.8442	0.8872	0.8624	0.8677	0.8650
0.0035	19.0	2318	0.8841	0.8897	0.8682	0.8645	0.8663
0.0013	20.0	2440	0.8886	0.8922	0.8719	0.8662	0.8690

Framework versions

Transformers 4.39.3
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.15.2