---
license: mit
tags:
- generated_from_trainer
datasets:
- id_clickbait
metrics:
- accuracy
model-index:
- name: clickbait-classifier-20230408-001
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: id_clickbait
      type: id_clickbait
      config: annotated
      split: train
      args: annotated
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7991666666666667
---

<!-- 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. -->

# clickbait-classifier-20230408-001

This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on the id_clickbait dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7645
- Accuracy: 0.7992

## 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4419        | 1.0   | 675  | 0.3934          | 0.8275   |
| 0.3611        | 2.0   | 1350 | 0.4369          | 0.8367   |
| 0.2017        | 3.0   | 2025 | 0.5936          | 0.8258   |
| 0.1369        | 4.0   | 2700 | 0.9894          | 0.8058   |
| 0.0941        | 5.0   | 3375 | 1.1425          | 0.82     |
| 0.0428        | 6.0   | 4050 | 1.3502          | 0.7958   |
| 0.0236        | 7.0   | 4725 | 1.4706          | 0.8058   |
| 0.0197        | 8.0   | 5400 | 1.6508          | 0.7975   |
| 0.0041        | 9.0   | 6075 | 1.7922          | 0.7967   |
| 0.0037        | 10.0  | 6750 | 1.7645          | 0.7992   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3