---
license: mit
base_model: openai-community/roberta-large-openai-detector
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
- f1
model-index:
- name: openai-roberta-large-AI-detection
  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. -->

# openai-roberta-large-AI-detection

This model is a fine-tuned version of [openai-community/roberta-large-openai-detector](https://huggingface.co/openai-community/roberta-large-openai-detector) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5761
- Accuracy: 0.7308
- Recall: 0.7513
- Precision: 0.7595
- F1: 0.7554

## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6973        | 1.0   | 197  | 0.5936          | 0.7071   | 0.9652 | 0.6612    | 0.7848 |
| 0.658         | 2.0   | 394  | 0.5761          | 0.7308   | 0.7513 | 0.7595    | 0.7554 |
| 0.4746        | 3.0   | 591  | 0.6044          | 0.7071   | 0.8690 | 0.6857    | 0.7665 |
| 0.3514        | 4.0   | 788  | 0.7278          | 0.7293   | 0.8636 | 0.7099    | 0.7793 |
| 0.2263        | 5.0   | 985  | 1.2186          | 0.7071   | 0.8636 | 0.6872    | 0.7654 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2