---
library_name: transformers
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: indobert-toxic-classifier
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# indobert-toxic-classifier

This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3947
- Accuracy: 0.8401
- F1: 0.8307
- Auc: 0.8236

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Auc    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
| 0.4145        | 1.0   | 1281 | 0.3739          | 0.8300   | 0.8123 | 0.8244 |
| 0.3639        | 2.0   | 2562 | 0.3726          | 0.8396   | 0.8150 | 0.8354 |
| 0.311         | 3.0   | 3843 | 0.3832          | 0.8414   | 0.8328 | 0.8386 |


### Framework versions

- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1