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

# classification-hate-speech-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: 1.9977
- F1 macro: 0.4920
- Weighted: 0.6769
- Balanced accuracy: 0.6391

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|
| 1.0988        | 1.0   | 162  | 1.0121          | 0.4279   | 0.6869   | 0.5200            |
| 0.7664        | 2.0   | 324  | 1.1188          | 0.4453   | 0.6992   | 0.5623            |
| 0.2422        | 3.0   | 486  | 1.0945          | 0.5639   | 0.7549   | 0.6537            |
| 0.0549        | 4.0   | 648  | 1.9487          | 0.4743   | 0.6351   | 0.6188            |
| 0.0054        | 5.0   | 810  | 2.0377          | 0.4754   | 0.6601   | 0.6356            |
| 0.0054        | 6.0   | 972  | 1.9811          | 0.4827   | 0.6734   | 0.6329            |
| 0.0047        | 7.0   | 1134 | 1.9977          | 0.4920   | 0.6769   | 0.6391            |


### Framework versions

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