---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Zidan_model_output_v4
  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. -->

# Zidan_model_output_v4

This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co./indolem/indobert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0719
- Accuracy: 0.8

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 248  | 1.1528          | 0.6727   |
| No log        | 2.0   | 496  | 0.8453          | 0.7273   |
| 0.9554        | 3.0   | 744  | 0.7237          | 0.7818   |
| 0.9554        | 4.0   | 992  | 0.8682          | 0.8      |
| 0.6805        | 5.0   | 1240 | 0.7821          | 0.7636   |
| 0.6805        | 6.0   | 1488 | 0.8538          | 0.7636   |
| 0.6217        | 7.0   | 1736 | 1.1071          | 0.7455   |
| 0.6217        | 8.0   | 1984 | 0.9356          | 0.8      |
| 0.5466        | 9.0   | 2232 | 0.9746          | 0.8182   |
| 0.5466        | 10.0  | 2480 | 1.1260          | 0.7818   |
| 0.4662        | 11.0  | 2728 | 1.0820          | 0.8      |
| 0.4662        | 12.0  | 2976 | 1.0719          | 0.8      |


### Framework versions

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