---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Zidan_model_output_v10
  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_v10

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: 0.7422
- Accuracy: 0.7455

## 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: 1e-06
- 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   | 248  | 1.0211          | 0.5273   |
| No log        | 2.0   | 496  | 0.9519          | 0.6727   |
| 1.0031        | 3.0   | 744  | 0.8800          | 0.6545   |
| 1.0031        | 4.0   | 992  | 0.8159          | 0.6909   |
| 0.8477        | 5.0   | 1240 | 0.8053          | 0.6909   |
| 0.8477        | 6.0   | 1488 | 0.8047          | 0.7455   |
| 0.7504        | 7.0   | 1736 | 0.7551          | 0.7455   |
| 0.7504        | 8.0   | 1984 | 0.7315          | 0.7273   |
| 0.6811        | 9.0   | 2232 | 0.7451          | 0.7273   |
| 0.6811        | 10.0  | 2480 | 0.7716          | 0.7273   |
| 0.6299        | 11.0  | 2728 | 0.7615          | 0.7636   |
| 0.6299        | 12.0  | 2976 | 0.7530          | 0.7455   |
| 0.5932        | 13.0  | 3224 | 0.7416          | 0.7455   |
| 0.5932        | 14.0  | 3472 | 0.7476          | 0.7455   |
| 0.5699        | 15.0  | 3720 | 0.7422          | 0.7455   |


### Framework versions

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