---
license: mit
base_model: roberta-base-openai-detector
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: artificially-natural-roberta
  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. -->

# artificially-natural-roberta

This model is a fine-tuned version of [roberta-base-openai-detector](https://huggingface.co/roberta-base-openai-detector) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1460
- F1: 0.98

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1    |
|:-------------:|:-----:|:----:|:---------------:|:-----:|
| No log        | 1.0   | 250  | 0.1378          | 0.971 |
| 0.1033        | 2.0   | 500  | 0.1073          | 0.985 |
| 0.1033        | 3.0   | 750  | 0.1460          | 0.98  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1