fine-tuned-IndoNLI-Translated-with-indobert-large-p2-LR-1e-05 – AI Model by muhammadravi251001 | AlphaNeural AI

You can deploy this model and start earning money today!

muhammadravi251001/
fine-tuned-IndoNLI-Translated-with-indobert-large-p2-LR-1e-05

like

0

text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

fine-tuned-IndoNLI-Translated-with-indobert-large-p2-LR-1e-05

This model is a fine-tuned version of indobenchmark/indobert-large-p2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6141
Accuracy: 0.8091
F1: 0.8096

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: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 128
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	F1
0.588	0.5	1533	0.5476	0.7836	0.7841
0.5415	1.0	3066	0.5186	0.8006	0.8014
0.4561	1.5	4599	0.5009	0.8088	0.8090
0.4711	2.0	6132	0.4981	0.8077	0.8071
0.4016	2.5	7665	0.5234	0.8057	0.8063
0.4101	3.0	9198	0.5096	0.8109	0.8114
0.3104	3.5	10731	0.5465	0.8113	0.8113
0.3256	4.0	12264	0.5440	0.8107	0.8113
0.2768	4.5	13797	0.6141	0.8091	0.8096

Framework versions

Transformers 4.29.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.2.0
Tokenizers 0.13.2