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license: apache-2.0
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# Model Card for Model ID

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

The model is fine-tuned from valurank/distilroberta-bias model for research purpose. 
## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->
The data used for fine-tuning is MBIC dataset, which contains texts with bias labels.

The model is capable of classifying any text into Biased or Non_biased. Max length set for the tokenizer is 512.




- **Developed by:** [More Information Needed]
- **Model type:** DistillRoBERTa transformer
- **Language(s) (NLP):** English
- **License:** Apache 2.0
- **Finetuned from model [optional]:** valurank/distilroberta-bias

### Model Sources [optional]

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- **Repository:** To be uploaded

### The following sections are under construction...


### 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

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[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:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

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

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[More Information Needed]

## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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[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