---
library_name: transformers
license: apache-2.0
base_model: unitary/toxic-bert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [unitary/toxic-bert](https://huggingface.co/unitary/toxic-bert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3031
- Accuracy: 64.2857
- Hamming Loss: 0.1111

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Hamming Loss |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------------:|
| 0.2107        | 1.0   | 11   | 0.3031          | 64.2857  | 0.1111       |
| 0.1632        | 2.0   | 22   | 0.3285          | 54.7619  | 0.1349       |
| 0.1236        | 3.0   | 33   | 0.3710          | 64.2857  | 0.0952       |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0