---
pipeline_tag: text-classification
library_name: transformers
tags:
- pytorch
base_model: microsoft/deberta-v3-small
datasets:
- webis/tldr-17
- yaful/MAGE
- liamdugan/raid
- lmarena-ai/arena-human-preference-140k
- lmarena-ai/arena-expert-5k
- KaiNylund/twitter-year-splits
- toloka/beemo
- gsingh1-py/train
language:
- en
license: cc-by-nc-4.0
---
# Investi-gator's V2 AI-Text Classifier (deBERTa-v3-small)

<!-- Provide a quick summary of what the model is/does. -->

On social media, it's very easy to run into posts that may not be authentic. This makes some question if the content their consuming is real or legitimate. For others it can lead them to consume misinformation or engage with users and content that don't have their best interest at heart. That's when Investi-gator steps in to help users take back control of their social media experience, using this model to classify content with AI generated text.

## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->
This model is specifically meant to classify text in a general or social media setting.


- **Developed by:** [bthomas279]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [English]
- **License:** [cc-by-nc-4.0]

### Training Scope 
Here's a list of the types of data used to train V2 of the AI-Text Detector
- Casual Reddit and Twitter Posts
- Answers to casual and expert questions
- AI -> Human paraphrasing
- AI & Human sounding sythetic posts (Claude, Gemini, ChatGPT, Grok, Deepseek


## Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->



[More Information Needed]

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

[More Information Needed]

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

Use the code below to get started with the model.

[More Information Needed]

## Training Details

### Training Data

<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->

[More Information Needed]

### Training Procedure

<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->

#### Preprocessing [optional]

[More Information Needed]


#### Training Hyperparameters

- **Training regime:** [fp32] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### Speeds, Sizes, Times [optional]

<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->

[More Information Needed]

## Evaluation

<!-- This section describes the evaluation protocols and provides the results. -->

### Testing Data, Factors & Metrics

#### Testing Data

<!-- This should link to a Dataset Card if possible. -->

[More Information Needed]

#### Factors

<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->

[More Information Needed]

#### Metrics

<!-- These are the evaluation metrics being used, ideally with a description of why. -->

[More Information Needed]

### Results

[More Information Needed]

#### Summary



## Model Examination [optional]

<!-- Relevant interpretability work for the model goes here -->

[More Information Needed]


## Technical Specifications [optional]

### Model Architecture and Objective

[More Information Needed]

### Compute Infrastructure

[More Information Needed]

#### Hardware

[More Information Needed]

#### Software

[More Information Needed]