metadata

license: mit
base_model: indobenchmark/indobert-lite-base-p1
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
language:
  - ind
datasets:
  - indonli
  - MoritzLaurer/multilingual-NLI-26lang-2mil7
  - LazarusNLP/multilingual-NLI-26lang-2mil7-id
widget:
  - text: Andi tersenyum karena mendapat hasil baik. </s></s> Andi sedih.
model-index:
  - name: indobert-lite-base-p1-indonli-multilingual-nli-distil-mdeberta
    results: []

IndoBERT Lite Base IndoNLI Multilingual NLI Distil mDeBERTa

IndoBERT Lite Base IndoNLI Multilingual NLI Distil mDeBERTa is a natural language inference (NLI) model based on the ALBERT model. The model was originally the pre-trained indobenchmark/indobert-lite-base-p1 model, which is then fine-tuned on IndoNLI and the Indonesian subsets of MoritzLaurer/multilingual-NLI-26lang-2mil7, whilst being distilled from MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7.

Evaluation Results

	`dev` Acc.	`test_lay` Acc.	`test_expert` Acc.
`IndoNLI`	78.60	74.69	65.55

Model

Model	#params	Arch.	Training/Validation data (text)
`indobert-lite-base-p1-indonli-multilingual-nli-distil-mdeberta`	11.7M	ALBERT Base	`IndoNLI`, Multilingual NLI (`id`)

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.4808	1.0	1803	0.4418	0.7683	0.7593	0.7904	0.7554
0.4529	2.0	3606	0.4343	0.7738	0.7648	0.7893	0.7619
0.4263	3.0	5409	0.4383	0.7861	0.7828	0.7874	0.7807
0.398	4.0	7212	0.4456	0.7792	0.7767	0.7792	0.7756
0.3772	5.0	9015	0.4499	0.7711	0.7674	0.7700	0.7661

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu121
Datasets 2.16.1
Tokenizers 0.15.0

References

[1] Mahendra, R., Aji, A. F., Louvan, S., Rahman, F., & Vania, C. (2021, November). IndoNLI: A Natural Language Inference Dataset for Indonesian. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics.