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

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: 2.6475
- F1 macro: 0.3742
- Weighted: 0.5772
- Balanced accuracy: 0.4995

## 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: 3e-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: 11

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 macro | Weighted | Balanced accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|
| 1.3987        | 1.0   | 152  | 1.1932          | 0.3716   | 0.6024   | 0.4578            |
| 0.8176        | 2.0   | 304  | 1.1670          | 0.4016   | 0.6136   | 0.4964            |
| 0.6289        | 3.0   | 456  | 1.2036          | 0.4099   | 0.6391   | 0.5131            |
| 0.1606        | 4.0   | 608  | 1.7535          | 0.3725   | 0.5728   | 0.5006            |
| 0.0285        | 5.0   | 760  | 1.8911          | 0.4152   | 0.6312   | 0.5199            |
| 0.0693        | 6.0   | 912  | 2.1700          | 0.4018   | 0.6026   | 0.5087            |
| 0.0047        | 7.0   | 1064 | 2.2234          | 0.3929   | 0.6128   | 0.5061            |
| 0.0032        | 8.0   | 1216 | 2.5087          | 0.3759   | 0.5816   | 0.4993            |
| 0.0025        | 9.0   | 1368 | 2.7507          | 0.3823   | 0.5547   | 0.5173            |
| 0.0016        | 10.0  | 1520 | 2.6432          | 0.3758   | 0.5808   | 0.5002            |
| 0.0012        | 11.0  | 1672 | 2.6475          | 0.3742   | 0.5772   | 0.4995            |


### Framework versions

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