---
library_name: transformers
license: mit
base_model: indobenchmark/indobert-base-p2
tags:
- generated_from_trainer
metrics:
- precision
- f1
model-index:
- name: indobert-smsa_doc-finetuned
  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. -->

# indobert-smsa_doc-finetuned

This model is a fine-tuned version of [indobenchmark/indobert-base-p2](https://huggingface.co/indobenchmark/indobert-base-p2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7818
- Precision: 0.9405
- F1: 0.9405

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.2174        | 1.0   | 2481 | 0.4282          | 0.9230    | 0.9230 |
| 0.0955        | 2.0   | 4962 | 0.7811          | 0.9405    | 0.9405 |
| 0.0435        | 3.0   | 7443 | 0.7818          | 0.9405    | 0.9405 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1