Update README.md

README.md

@@ -8,59 +8,57 @@ metrics:
 - 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: []
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+# IndoBERT Lite Base IndoNLI Multilingual NLI Distil mDeBERTa
 
-# indobert-lite-base-p1-indonli-multilingual-nli-distil-mdeberta
+IndoBERT Lite Base IndoNLI Multilingual NLI Distil mDeBERTa is a natural language inference (NLI) model based on the [ALBERT](https://arxiv.org/abs/1909.11942) model. The model was originally the pre-trained [indobenchmark/indobert-lite-base-p1](https://huggingface.co/indobenchmark/indobert-lite-base-p1) model, which is then fine-tuned on [`IndoNLI`](https://github.com/ir-nlp-csui/indonli) and the [Indonesian subsets](https://huggingface.co/datasets/LazarusNLP/multilingual-NLI-26lang-2mil7-id) of [MoritzLaurer/multilingual-NLI-26lang-2mil7](https://huggingface.co/datasets/MoritzLaurer/multilingual-NLI-26lang-2mil7), whilst being distilled from [MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7).
 
-This model is a fine-tuned version of [indobenchmark/indobert-lite-base-p1](https://huggingface.co/indobenchmark/indobert-lite-base-p1) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.5005
-- Accuracy: 0.6545
-- F1: 0.6524
-- Precision: 0.6615
-- Recall: 0.6577
+## Evaluation Results
 
-## Model description
+|           | `dev` Acc. | `test_lay` Acc. | `test_expert` Acc. |
+| --------- | :--------: | :-------------: | :----------------: |
+| `IndoNLI` |   78.60    |      74.69      |       65.55        |
 
-More information needed
+## Model
 
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
+| 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
+- `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 |
-
+| 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
 
@@ -68,3 +66,7 @@ The following hyperparameters were used during training:
 - 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](https://arxiv.org/abs/2110.14566). _Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing_. Association for Computational Linguistics.