---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: ROS-text-classification
  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. -->

# ROS-text-classification

This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8096
- Balanced Accuracy: 0.7524

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Balanced Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|
| 1.4134        | 1.0   | 139  | 1.2061          | 0.5871            |
| 0.7846        | 2.0   | 278  | 0.9400          | 0.6932            |
| 0.6999        | 3.0   | 417  | 0.8096          | 0.7524            |
| 0.3644        | 4.0   | 556  | 0.8431          | 0.7721            |
| 0.3832        | 5.0   | 695  | 0.9038          | 0.7594            |
| 0.2631        | 6.0   | 834  | 1.0126          | 0.7800            |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1