---
license: apache-2.0
base_model: indolem/indobertweet-base-uncased
tags:
- generated_from_trainer
model-index:
- name: classification-hate-speech-4
  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-4

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: 2.3401
- F1 macro: 0.4271
- Weighted: 0.5984
- Balanced accuracy: 0.5716

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|
| 1.2531        | 1.0   | 152  | 1.0752          | 0.3830   | 0.6537   | 0.4508            |
| 0.8066        | 2.0   | 304  | 1.1219          | 0.3948   | 0.6504   | 0.4784            |
| 0.2886        | 3.0   | 456  | 1.7797          | 0.3590   | 0.5719   | 0.4879            |
| 0.0446        | 4.0   | 608  | 2.0984          | 0.4186   | 0.5843   | 0.5796            |
| 0.0564        | 5.0   | 760  | 2.4550          | 0.4082   | 0.5537   | 0.5473            |
| 0.0123        | 6.0   | 912  | 2.2256          | 0.4187   | 0.6068   | 0.5640            |
| 0.0035        | 7.0   | 1064 | 2.3401          | 0.4271   | 0.5984   | 0.5716            |


### Framework versions

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