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---
license: apache-2.0
base_model: indolem/indobertweet-base-uncased
tags:
- generated_from_trainer
model-index:
- name: nasiuduk2024_indobtwt_7_reprsample_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. -->

# nasiuduk2024_indobtwt_7_reprsample_2

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: 1.8928
- F1 macro: 0.4060
- Weighted: 0.6825
- Balanced accuracy: 0.4640

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|
| 1.2738        | 1.0   | 206  | 0.9566          | 0.3914   | 0.6845   | 0.4444            |
| 1.1101        | 2.0   | 412  | 0.9996          | 0.4091   | 0.6819   | 0.4812            |
| 0.3331        | 3.0   | 618  | 1.3851          | 0.4014   | 0.6480   | 0.4958            |
| 0.2889        | 4.0   | 824  | 1.5148          | 0.4136   | 0.6882   | 0.4686            |
| 0.0132        | 5.0   | 1030 | 1.8454          | 0.3969   | 0.6668   | 0.4753            |
| 0.0822        | 6.0   | 1236 | 2.0285          | 0.4064   | 0.6664   | 0.4908            |
| 0.003         | 7.0   | 1442 | 1.8928          | 0.4060   | 0.6825   | 0.4640            |


### Framework versions

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