---
license: apache-2.0
base_model: indolem/indobertweet-base-uncased
tags:
- generated_from_trainer
model-index:
- name: classification-hate-speech-3
  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-3

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: 2.5282
- F1 macro: 0.3639
- Weighted: 0.5795
- Balanced accuracy: 0.4853

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|
| 1.2772        | 1.0   | 162  | 1.3236          | 0.3758   | 0.6336   | 0.4617            |
| 0.9542        | 2.0   | 324  | 1.3274          | 0.3523   | 0.5765   | 0.4628            |
| 0.2508        | 3.0   | 486  | 1.2635          | 0.4108   | 0.6672   | 0.4862            |
| 0.0771        | 4.0   | 648  | 1.8577          | 0.3926   | 0.6303   | 0.5001            |
| 0.0063        | 5.0   | 810  | 2.4522          | 0.3539   | 0.5700   | 0.4784            |
| 0.0053        | 6.0   | 972  | 2.3522          | 0.3682   | 0.6028   | 0.4759            |
| 0.004         | 7.0   | 1134 | 2.5282          | 0.3639   | 0.5795   | 0.4853            |


### Framework versions

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