---
license: mit
base_model: openai-community/roberta-base-openai-detector
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: train_debug
  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. -->

# train_debug

This model is a fine-tuned version of [openai-community/roberta-base-openai-detector](https://huggingface.co/openai-community/roberta-base-openai-detector) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0098
- Accuracy: 0.999
- Roc Auc: 1.0000

## 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: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Roc Auc |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|
| 0.0336        | 1.0   | 6250  | 0.0298          | 0.992    | 0.9999  |
| 0.0085        | 2.0   | 12500 | 0.0098          | 0.999    | 1.0000  |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0