---
license: apache-2.0
base_model: indolem/indobertweet-base-uncased
tags:
- generated_from_trainer
model-index:
- name: nasiuduk2024_indobtwt_7_u_o
  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. -->

# nasiuduk2024_indobtwt_7_u_o

This model is a fine-tuned version of [indolem/indobertweet-base-uncased](https://huggingface.co/indolem/indobertweet-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5305
- F1 macro: 0.3802
- Weighted: 0.5879
- Balanced accuracy: 0.5179

## 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 macro | Weighted | Balanced accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|
| 1.4191        | 1.0   | 162  | 1.3702          | 0.3358   | 0.5319   | 0.4757            |
| 0.6762        | 2.0   | 324  | 1.3777          | 0.3590   | 0.5807   | 0.4857            |
| 0.4675        | 3.0   | 486  | 1.5368          | 0.4526   | 0.5879   | 0.5707            |
| 0.1559        | 4.0   | 648  | 2.3060          | 0.3595   | 0.5416   | 0.4922            |
| 0.0104        | 5.0   | 810  | 2.2064          | 0.3881   | 0.6050   | 0.5170            |
| 0.0076        | 6.0   | 972  | 2.4857          | 0.3849   | 0.5892   | 0.5210            |
| 0.0025        | 7.0   | 1134 | 2.5305          | 0.3802   | 0.5879   | 0.5179            |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1