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---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: text-classification
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. -->
# text-classification
This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co./indolem/indobert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9158
- Accuracy: 0.7695
## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0037 | 1.0 | 499 | 1.0119 | 0.7024 |
| 0.7645 | 2.0 | 998 | 0.9929 | 0.7275 |
| 0.6417 | 3.0 | 1497 | 0.9623 | 0.7335 |
| 0.8177 | 4.0 | 1996 | 0.9158 | 0.7695 |
| 0.4176 | 5.0 | 2495 | 1.2640 | 0.7635 |
| 0.7335 | 6.0 | 2994 | 1.2080 | 0.7615 |
| 0.3151 | 7.0 | 3493 | 1.3485 | 0.7575 |
| 0.7147 | 8.0 | 3992 | 1.2736 | 0.7605 |
| 0.0728 | 9.0 | 4491 | 1.4076 | 0.7565 |
| 0.2183 | 10.0 | 4990 | 1.5012 | 0.7505 |
| 0.2202 | 11.0 | 5489 | 1.5981 | 0.7405 |
| 0.2694 | 12.0 | 5988 | 1.5516 | 0.7415 |
| 0.0497 | 13.0 | 6487 | 1.6425 | 0.7485 |
| 0.2473 | 14.0 | 6986 | 1.7087 | 0.7475 |
| 0.1949 | 15.0 | 7485 | 1.6820 | 0.7535 |
| 0.1233 | 16.0 | 7984 | 1.7447 | 0.7405 |
| 0.0632 | 17.0 | 8483 | 1.7229 | 0.7475 |
| 0.1161 | 18.0 | 8982 | 1.7292 | 0.7545 |
| 0.0023 | 19.0 | 9481 | 1.7930 | 0.7465 |
| 0.0854 | 20.0 | 9980 | 1.8089 | 0.7495 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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