---
library_name: transformers
license: mit
base_model: openai-community/roberta-base-openai-detector
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: AI_Human_Text_Detection_40K_roberta-base-openai-detector
  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. -->

# AI_Human_Text_Detection_40K_roberta-base-openai-detector

This model is a fine-tuned version of [openai-community/roberta-base-openai-detector](https://huggingface.co/openai-community/roberta-base-openai-detector) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1859
- Accuracy: 0.66

## 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: 8
- eval_batch_size: 8
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1525        | 1.0   | 4500  | 2.9892          | 0.6142   |
| 0.1047        | 2.0   | 9000  | 2.2166          | 0.706    |
| 0.0524        | 3.0   | 13500 | 2.4719          | 0.691    |
| 0.0205        | 4.0   | 18000 | 3.1859          | 0.66     |


### Framework versions

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