---
library_name: transformers
license: mit
base_model: indobenchmark/indobert-large-p2
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: results_indobert-large-p2_preprocessing_tuning
  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. -->

# results_indobert-large-p2_preprocessing_tuning

This model is a fine-tuned version of [indobenchmark/indobert-large-p2](https://huggingface.co/indobenchmark/indobert-large-p2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6673
- Accuracy: 0.7841
- Precision: 0.7920
- Recall: 0.7918
- F1: 0.7901

## 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: 2.3352320097915953e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.2207        | 1.0   | 111  | 0.7383          | 0.7409   | 0.7463    | 0.7491 | 0.7435 |
| 0.6702        | 2.0   | 222  | 0.6673          | 0.7841   | 0.7920    | 0.7918 | 0.7901 |
| 0.4953        | 3.0   | 333  | 0.7161          | 0.7636   | 0.7707    | 0.7722 | 0.7711 |
| 0.3754        | 4.0   | 444  | 0.8318          | 0.75     | 0.7552    | 0.7657 | 0.7569 |
| 0.2769        | 5.0   | 555  | 0.8916          | 0.7591   | 0.7587    | 0.7732 | 0.7642 |
| 0.2039        | 6.0   | 666  | 0.9693          | 0.7432   | 0.7533    | 0.7589 | 0.7524 |
| 0.1525        | 7.0   | 777  | 1.0838          | 0.7477   | 0.7431    | 0.7610 | 0.7471 |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2