fine-tuned-IndoNLI-Basic-with-indobert-large-p2 – AI Model by afaji | AlphaNeural AI

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fine-tuned-IndoNLI-Basic-with-indobert-large-p2

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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fine-tuned-IndoNLI-Basic-with-indobert-large-p2

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: 1.2497
Accuracy: 0.7751

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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
num_epochs: 16

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.978	1.0	161	0.8505	0.6236
0.6752	2.0	322	0.6163	0.7542
0.5579	3.0	483	0.6259	0.7551
0.4328	4.0	644	0.6153	0.7706
0.3217	5.0	805	0.6348	0.7711
0.229	6.0	966	0.7245	0.7720
0.1688	7.0	1127	0.8032	0.7774
0.1258	8.0	1288	0.8898	0.7742
0.0942	9.0	1449	0.9629	0.7651
0.0718	10.0	1610	0.9848	0.7783
0.0635	11.0	1771	1.0794	0.7674
0.0407	12.0	1932	1.1378	0.7679
0.0394	13.0	2093	1.2195	0.7651
0.0323	14.0	2254	1.2151	0.7756
0.0235	15.0	2415	1.2509	0.7711
0.0277	16.0	2576	1.2497	0.7751

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu117
Datasets 2.2.0
Tokenizers 0.13.2