---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Zidan_model_output_80_10_10
  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_80_10_10

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: 1.8090
- Accuracy: 0.7273

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data



## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 220  | 0.6488          | 0.7455   |
| No log        | 2.0   | 440  | 0.7206          | 0.7364   |
| 0.6877        | 3.0   | 660  | 0.9170          | 0.7818   |
| 0.6877        | 4.0   | 880  | 1.2220          | 0.7455   |
| 0.2623        | 5.0   | 1100 | 1.6100          | 0.7364   |
| 0.2623        | 6.0   | 1320 | 1.8847          | 0.6818   |
| 0.0832        | 7.0   | 1540 | 1.8377          | 0.6909   |
| 0.0832        | 8.0   | 1760 | 1.6139          | 0.7182   |
| 0.0832        | 9.0   | 1980 | 1.9268          | 0.7      |
| 0.0502        | 10.0  | 2200 | 1.8679          | 0.7182   |
| 0.0502        | 11.0  | 2420 | 1.8020          | 0.7364   |
| 0.0311        | 12.0  | 2640 | 1.7905          | 0.7273   |
| 0.0311        | 13.0  | 2860 | 1.7716          | 0.7364   |
| 0.0252        | 14.0  | 3080 | 1.8070          | 0.7273   |
| 0.0252        | 15.0  | 3300 | 1.8090          | 0.7273   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1