---
license: mit
base_model: indobenchmark/indobert-base-p2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: aspect_model
  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. -->

# aspect_model

This model is a fine-tuned version of [indobenchmark/indobert-base-p2](https://huggingface.co/indobenchmark/indobert-base-p2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3490
- Accuracy: 0.8084

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 72   | 0.6516          | 0.7735   |
| No log        | 2.0   | 144  | 0.6119          | 0.7909   |
| No log        | 3.0   | 216  | 0.6152          | 0.8049   |
| No log        | 4.0   | 288  | 0.7480          | 0.8118   |
| No log        | 5.0   | 360  | 1.0121          | 0.7770   |
| No log        | 6.0   | 432  | 1.0780          | 0.7909   |
| 0.27          | 7.0   | 504  | 1.1602          | 0.7840   |
| 0.27          | 8.0   | 576  | 1.2136          | 0.8014   |
| 0.27          | 9.0   | 648  | 1.2490          | 0.8014   |
| 0.27          | 10.0  | 720  | 1.3102          | 0.7840   |
| 0.27          | 11.0  | 792  | 1.3184          | 0.8049   |
| 0.27          | 12.0  | 864  | 1.3255          | 0.8014   |
| 0.27          | 13.0  | 936  | 1.3192          | 0.8049   |
| 0.0022        | 14.0  | 1008 | 1.3229          | 0.7944   |
| 0.0022        | 15.0  | 1080 | 1.3415          | 0.8014   |
| 0.0022        | 16.0  | 1152 | 1.3515          | 0.7909   |
| 0.0022        | 17.0  | 1224 | 1.3544          | 0.7944   |
| 0.0022        | 18.0  | 1296 | 1.3529          | 0.7944   |
| 0.0022        | 19.0  | 1368 | 1.3484          | 0.8084   |
| 0.0022        | 20.0  | 1440 | 1.3490          | 0.8084   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0