---
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: stunting-medsos-sentiment
  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. -->

# stunting-medsos-sentiment

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: 0.9685
- Accuracy: 0.8360
- Precision: 0.7971
- Recall: 0.7985
- F1: 0.7976

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 314  | 0.5221          | 0.8105   | 0.7868    | 0.7345 | 0.7517 |
| 0.5607        | 2.0   | 628  | 0.6322          | 0.8296   | 0.7991    | 0.7670 | 0.7794 |
| 0.5607        | 3.0   | 942  | 0.9147          | 0.8201   | 0.7929    | 0.7655 | 0.7731 |
| 0.2289        | 4.0   | 1256 | 0.9736          | 0.8296   | 0.7929    | 0.7990 | 0.7957 |
| 0.0597        | 5.0   | 1570 | 0.9685          | 0.8360   | 0.7971    | 0.7985 | 0.7976 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1