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---
license: mit
base_model: ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: best_bert_model_fold_2
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. -->
# best_bert_model_fold_2
This model is a fine-tuned version of [ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa](https://huggingface.co/ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1931
- Accuracy: 0.8606
- Precision: 0.8353
- Recall: 0.8104
- F1: 0.8211
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 1.0 | 252 | 0.5154 | 0.8347 | 0.8228 | 0.7436 | 0.7630 |
| 0.5197 | 2.0 | 504 | 0.5658 | 0.8466 | 0.8122 | 0.7892 | 0.7981 |
| 0.5197 | 3.0 | 756 | 0.8319 | 0.8526 | 0.8328 | 0.7857 | 0.8007 |
| 0.1558 | 4.0 | 1008 | 0.8339 | 0.8526 | 0.8230 | 0.8138 | 0.8180 |
| 0.1558 | 5.0 | 1260 | 1.0511 | 0.8486 | 0.8241 | 0.7922 | 0.8052 |
| 0.0472 | 6.0 | 1512 | 1.1080 | 0.8546 | 0.8313 | 0.8008 | 0.8135 |
| 0.0472 | 7.0 | 1764 | 1.1492 | 0.8566 | 0.8315 | 0.8093 | 0.8189 |
| 0.005 | 8.0 | 2016 | 1.1661 | 0.8566 | 0.8289 | 0.8084 | 0.8175 |
| 0.005 | 9.0 | 2268 | 1.1931 | 0.8606 | 0.8353 | 0.8104 | 0.8211 |
| 0.0031 | 10.0 | 2520 | 1.1820 | 0.8586 | 0.8335 | 0.8020 | 0.8149 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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