best_bert_model_fold_4 – AI Model by choiruzzia | AlphaNeural AI

You can deploy this model and start earning money today!

choiruzzia/
best_bert_model_fold_4

like

0

text-classification

generated_from_trainer

ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa

autotrain_compatible

endpoints_compatible

Views

No views yet

best_bert_model_fold_4

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: 0.6077
Accuracy: 0.8187
Precision: 0.7940
Recall: 0.7673
F1: 0.7780

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
No log	1.0	252	0.5413	0.8088	0.7842	0.7520	0.7641
0.5338	2.0	504	0.6077	0.8187	0.7940	0.7673	0.7780
0.5338	3.0	756	0.9325	0.7928	0.7597	0.7270	0.7357
0.1829	4.0	1008	1.1287	0.8068	0.7916	0.7662	0.7763
0.1829	5.0	1260	1.2985	0.7988	0.7700	0.7688	0.7676
0.0459	6.0	1512	1.5210	0.8108	0.7837	0.7721	0.7773
0.0459	7.0	1764	1.5855	0.8028	0.7799	0.7611	0.7680
0.0097	8.0	2016	1.5212	0.8008	0.7684	0.7731	0.7706
0.0097	9.0	2268	1.5775	0.8028	0.7730	0.7656	0.7682
0.0001	10.0	2520	1.5819	0.8048	0.7746	0.7669	0.7698

Framework versions

Transformers 4.41.2
Pytorch 2.1.2
Datasets 2.19.2
Tokenizers 0.19.1