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

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: 2.3971
- F1 macro: 0.3764
- Weighted: 0.5676
- Balanced accuracy: 0.5202

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|
| 1.1881        | 1.0   | 98   | 1.2881          | 0.3632   | 0.5818   | 0.4714            |
| 0.9442        | 2.0   | 196  | 1.6041          | 0.3525   | 0.4977   | 0.5128            |
| 0.5045        | 3.0   | 294  | 2.1271          | 0.3236   | 0.4088   | 0.5040            |
| 0.111         | 4.0   | 392  | 1.9956          | 0.3627   | 0.5579   | 0.5034            |
| 0.0279        | 5.0   | 490  | 2.3665          | 0.3740   | 0.5627   | 0.5203            |
| 0.0203        | 6.0   | 588  | 2.4468          | 0.3662   | 0.5512   | 0.5170            |
| 0.006         | 7.0   | 686  | 2.3971          | 0.3764   | 0.5676   | 0.5202            |


### Framework versions

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