---
license: mit
base_model: indobenchmark/indobert-large-p2
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: indonli-indobert-large
  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. -->

# indonli-indobert-large

This model is a fine-tuned version of [indobenchmark/indobert-large-p2](https://huggingface.co/indobenchmark/indobert-large-p2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9753
- Accuracy: 0.6350
- Precision: 0.6350
- Recall: 0.6350
- F1 Score: 0.6362

## 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: 3e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 101
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1 Score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 1.0324        | 1.0   | 2583  | 0.9492          | 0.5508   | 0.5508    | 0.5508 | 0.5172   |
| 0.9234        | 2.0   | 5166  | 0.8837          | 0.6099   | 0.6099    | 0.6099 | 0.6106   |
| 0.8318        | 3.0   | 7749  | 0.8718          | 0.6277   | 0.6277    | 0.6277 | 0.6302   |
| 0.7417        | 4.0   | 10332 | 0.9005          | 0.6313   | 0.6313    | 0.6313 | 0.6326   |
| 0.6788        | 5.0   | 12915 | 0.9380          | 0.6368   | 0.6368    | 0.6368 | 0.6381   |
| 0.6263        | 6.0   | 15498 | 0.9753          | 0.6350   | 0.6350    | 0.6350 | 0.6362   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3