---
license: mit
base_model: indobenchmark/indobart-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bdc2024-indobert-1
  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. -->

# bdc2024-indobert-1

This model is a fine-tuned version of [indobenchmark/indobart-v2](https://huggingface.co/indobenchmark/indobart-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4102
- Accuracy: 0.9273
- Balanced Accuracy: 0.8413
- Precision: 0.9275
- Recall: 0.9273
- F1: 0.9216

## 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 | Balanced Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:---------:|:------:|:------:|
| No log        | 1.0   | 483  | 0.7392          | 0.7686   | 0.4854            | 0.7372    | 0.7686 | 0.7356 |
| 0.7636        | 2.0   | 966  | 0.5057          | 0.8547   | 0.6601            | 0.8589    | 0.8547 | 0.8347 |
| 0.4764        | 3.0   | 1449 | 0.4090          | 0.9120   | 0.7949            | 0.9156    | 0.9120 | 0.9035 |
| 0.27          | 4.0   | 1932 | 0.4089          | 0.9273   | 0.8411            | 0.9273    | 0.9273 | 0.9221 |
| 0.1442        | 5.0   | 2415 | 0.4102          | 0.9273   | 0.8413            | 0.9275    | 0.9273 | 0.9216 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.13.3