---
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-distil
  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-p1-indonli-distil

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: 0.5443
- Accuracy: 0.6123
- F1: 0.6060
- Precision: 0.6275
- Recall: 0.6184

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5053        | 1.0   | 646  | 0.4511          | 0.7506   | 0.7462 | 0.7530    | 0.7445 |
| 0.4516        | 2.0   | 1292 | 0.4458          | 0.7692   | 0.7683 | 0.7684    | 0.7697 |
| 0.4192        | 3.0   | 1938 | 0.4433          | 0.7701   | 0.7677 | 0.7685    | 0.7673 |
| 0.3647        | 4.0   | 2584 | 0.4497          | 0.7720   | 0.7699 | 0.7697    | 0.7701 |
| 0.3502        | 5.0   | 3230 | 0.4530          | 0.7679   | 0.7661 | 0.7658    | 0.7668 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0