---
license: mit
base_model: indobenchmark/indobert-base-p2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: gacha_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. -->

# gacha_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: 0.4437
- Accuracy: 0.8065
- F1: 0.7877
- Precision: 0.8105
- Recall: 0.7662

## 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 | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 215  | 0.4437          | 0.8065   | 0.7877 | 0.8105    | 0.7662 |
| No log        | 2.0   | 430  | 0.4728          | 0.8042   | 0.7766 | 0.8343    | 0.7264 |
| 0.343         | 3.0   | 645  | 0.7781          | 0.8089   | 0.7940 | 0.8020    | 0.7861 |
| 0.343         | 4.0   | 860  | 0.9427          | 0.8089   | 0.7842 | 0.8324    | 0.7413 |
| 0.0974        | 5.0   | 1075 | 1.1330          | 0.8089   | 0.7807 | 0.8439    | 0.7264 |
| 0.0974        | 6.0   | 1290 | 1.2451          | 0.8019   | 0.7781 | 0.8187    | 0.7413 |
| 0.0187        | 7.0   | 1505 | 1.2750          | 0.8205   | 0.7958 | 0.8523    | 0.7463 |
| 0.0187        | 8.0   | 1720 | 1.3551          | 0.8135   | 0.7849 | 0.8538    | 0.7264 |
| 0.0187        | 9.0   | 1935 | 1.3652          | 0.8205   | 0.7979 | 0.8444    | 0.7562 |
| 0.0018        | 10.0  | 2150 | 1.4262          | 0.8112   | 0.7817 | 0.8529    | 0.7214 |


### Framework versions

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