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LazarusNLP/indobert-lite-base-p1-indonli-multilingual-nli-distil-mdeberta
indobert-lite-base-p1-indonli-multilingual-nli-distil-mdeberta is a text classification model from LazarusNLP. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
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, wh…
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From the Hugging Face model README
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.
dev Acc. | test_lay Acc. | test_expert Acc. | |
|---|---|---|---|
IndoNLI | 78.60 | 74.69 | 65.55 |
| Model | #params | Arch. | Training/Validation data (text) |
|---|---|---|---|
indobert-lite-base-p1-indonli-multilingual-nli-distil-mdeberta | 11.7M | ALBERT Base | IndoNLI, Multilingual NLI (id) |
The following hyperparameters were used during training:
learning_rate: 2e-05train_batch_size: 64eval_batch_size: 64seed: 42optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08lr_scheduler_type: linearnum_epochs: 5| 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 |
[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.