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---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Kemenkeu-Sentiment-Classifier
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. -->
# Kemenkeu-Sentiment-Classifier
This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co./indobenchmark/indobert-base-p1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8733
- Accuracy: 0.64
- F1: 0.5936
## 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-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0146 | 1.0 | 500 | 0.8733 | 0.64 | 0.5936 |
| 0.7047 | 2.0 | 1000 | 0.8814 | 0.634 | 0.6008 |
| 0.5002 | 3.0 | 1500 | 0.9076 | 0.668 | 0.6446 |
| 0.3531 | 4.0 | 2000 | 0.9730 | 0.664 | 0.6374 |
### Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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