fine-tuned-IndoNLI-Basic-with-indobert-base-uncased – AI Model by muhammadravi251001 | AlphaNeural AI

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fine-tuned-IndoNLI-Basic-with-indobert-base-uncased

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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fine-tuned-IndoNLI-Basic-with-indobert-base-uncased

This model is a fine-tuned version of indolem/indobert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6336
Accuracy: 0.7779

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: 16
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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0949	1.0	161	0.9773	0.4980
0.8844	2.0	322	0.7456	0.6859
0.7276	3.0	483	0.6554	0.7437
0.6326	4.0	644	0.6124	0.7615
0.5654	5.0	805	0.6057	0.7656
0.5108	6.0	966	0.6196	0.7747
0.4741	7.0	1127	0.6219	0.7738
0.4388	8.0	1288	0.6241	0.7783
0.4128	9.0	1449	0.6329	0.7792
0.3964	10.0	1610	0.6336	0.7779

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu117
Datasets 2.2.0
Tokenizers 0.13.2