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---
license: mit
base_model: indobenchmark/indobert-base-p1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: indobert-finetuned-sentiment-happiness-index
results: []
widget:
- text: Aku suka makan bakso
example_title: Sentiment Analysis
language:
- id
pipeline_tag: text-classification
---
<!-- 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. -->
# indobert-finetuned-sentiment-happiness-index
This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co./indobenchmark/indobert-base-p1) on an own private dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4094
- Accuracy: 0.8048
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 270 | 0.5214 | 0.7900 |
| 0.5321 | 2.0 | 540 | 0.6425 | 0.7475 |
| 0.5321 | 3.0 | 810 | 0.7702 | 0.7835 |
| 0.1711 | 4.0 | 1080 | 1.0106 | 0.7937 |
| 0.1711 | 5.0 | 1350 | 1.2141 | 0.7891 |
| 0.0508 | 6.0 | 1620 | 1.3340 | 0.7965 |
| 0.0508 | 7.0 | 1890 | 1.3483 | 0.8030 |
| 0.0133 | 8.0 | 2160 | 1.3591 | 0.8085 |
| 0.0133 | 9.0 | 2430 | 1.4149 | 0.8057 |
| 0.0055 | 10.0 | 2700 | 1.4094 | 0.8048 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3 |