---
license: mit
base_model: indobenchmark/indobert-lite-base-p1
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
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
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# indobert-lite-base-p1-indonli-multilingual-nli-distil-mdeberta

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

## 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: 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