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  # Model Card for Model ID
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- <!-- Provide a quick summary of what the model is/does. -->
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  ## Model Details
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- ### Model Description
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- <!-- Provide a longer summary of what this model is. -->
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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- ### Model Sources [optional]
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- <!-- Provide the basic links for the model. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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- ## Uses
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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- ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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- ### Downstream Use [optional]
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- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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- [More Information Needed]
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  ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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  [More Information Needed]
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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  ## How to Get Started with the Model
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  [More Information Needed]
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- ### Training Procedure
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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- #### Preprocessing [optional]
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- [More Information Needed]
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  #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- #### Speeds, Sizes, Times [optional]
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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- [More Information Needed]
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  ## Evaluation
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- <!-- This section describes the evaluation protocols and provides the results. -->
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- <!-- This should link to a Dataset Card if possible. -->
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  [More Information Needed]
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- #### Factors
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- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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- [More Information Needed]
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- #### Metrics
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- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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  ### Results
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- #### Summary
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- ## Model Examination [optional]
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- <!-- Relevant interpretability work for the model goes here -->
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- [More Information Needed]
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- ## Environmental Impact
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- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- - **Hardware Type:** [More Information Needed]
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- - **Hours used:** [More Information Needed]
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- - **Cloud Provider:** [More Information Needed]
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- - **Compute Region:** [More Information Needed]
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- - **Carbon Emitted:** [More Information Needed]
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- ### Compute Infrastructure
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- #### Hardware
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- #### Software
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- ## Citation [optional]
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- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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- **BibTeX:**
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- **APA:**
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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- [More Information Needed]
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- ## More Information [optional]
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- ## Model Card Authors [optional]
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- ## Model Card Contact
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  # Model Card for Model ID
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+ This model is a fine-tuned version of [XLM-R Large](https://huggingface.co/FacebookAI/xlm-roberta-large). It is trained to classify common disinformation narratives, a task that is important to automated fact-checking. It was trained in a weakly-supervised fashion using GPT-4o. The datasets are German, however, the underlying model is multilingual. It was not tested how the model performs in other languages. For testing a sample of fact-checks from German fact-checking organizations was inspected and if the checked claim supported one of the narratives, the social media posts with the original text were extracted.
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  ## Model Details
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  ## Bias, Risks, and Limitations
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  [More Information Needed]
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  ## How to Get Started with the Model
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  [More Information Needed]
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  #### Training Hyperparameters
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+ - Epochs: 10
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+ - Batch size: 16
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+ - learning_rate: 2e-5
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+ - weight_decay: 0.01
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+ - fp16: True
 
 
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  ## Evaluation
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+ ### Testing Data
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  [More Information Needed]
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  ### Results
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+ | Category | Precision | Recall | F1-Score | Support |
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+ |------------------------------------------------------------------------------------------------------------------------------|:---------:|:------:|:--------:|:-------:|
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+ | 5G verursacht Krankheiten für Menschen und Tiere. | 1.00 | 0.83 | 0.91 | 6 |
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+ | Ausländer sind krimineller als Deutsche, werden geringer bestraft und begehen mehr Straftaten, und das wird uns verheimlicht. | 1.00 | 0.67 | 0.80 | 3 |
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+ | Ausländer und Migranten bekommen mehr Leistungen oder Wohnungen vom Staat als Deutsche. | 1.00 | 1.00 | 1.00 | 9 |
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+ | Bargeld soll abgeschafft werden. | 0.67 | 1.00 | 0.80 | 2 |
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+ | Das Wetter war früher überhaupt nicht anders und Naturphänomene wie Vulkanausbrüche sind schuld am Klimawandel. | 1.00 | 1.00 | 1.00 | 7 |
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+ | Der Anteil des Menschen an den Treibhausgasen ist nur gering und die Wahrheit über den Klimawandel wird verheimlicht. | 1.00 | 1.00 | 1.00 | 7 |
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+ | Der WHO-Pandemievertrag hebt die Souveränität von Staaten auf und führt zu einer WHO-Diktatur. | 1.00 | 1.00 | 1.00 | 1 |
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+ | Der Westen hat ein Friedensabkommen zwischen Russland und der Ukraine verhindert. | 0.00 | 0.00 | 0.00 | 0 |
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+ | Deutschland wird von Faschisten regiert. | 1.00 | 1.00 | 1.00 | 1 |
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+ | Die Covid-19-Impfung ist nicht ausreichend erforscht und verursacht Nebenwirkungen. | 0.91 | 0.83 | 0.87 | 12 |
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+ | Die Regierung will gezielt Migranten ins Land holen und schickt Geld ins Ausland während unsere Leute leiden. | 0.67 | 1.00 | 0.80 | 2 |
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+ | Die Stimmzettel, Urnen und Briefwahl sind manipuliert und Wahlhelfer lassen Stimmen verschwinden. | 1.00 | 1.00 | 1.00 | 16 |
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+ | Die Wahrheit über die Corona-Maßnahmen, Todesopfer und Covid-Impfung wird verheimlicht. | 0.75 | 1.00 | 0.86 | 3 |
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+ | E-Mobilität ist schlechter für die Umwelt als Verbrenner Autos. | 1.00 | 1.00 | 1.00 | 2 |
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+ | Gewisse Lebensmittel, Leitungswasser oder Gentechnik sind gesundheitsschädlich und machen unfruchtbar. | 1.00 | 1.00 | 1.00 | 10 |
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+ | Hilfsgüter an die Ukraine werden in Wahrheit weggeworfen oder zerstört. | 1.00 | 1.00 | 1.00 | 3 |
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+ | Keins der Narrative trifft zu. | 0.00 | 0.00 | 0.00 | 0 |
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+ | Selensky ist korrupt und drogenabhängig und die Ukraine wird von Nazis regiert. | 1.00 | 0.33 | 0.50 | 3 |
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+ | Windräder töten hunderttausende Vögel, verursachen Luftwirbel und Dürre und es werden Wälder für die Windräder gerohdet. | 1.00 | 1.00 | 1.00 | 9 |
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+ | **Accuracy** | | | 0.94 | 96 |
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+ | **Macro avg** | 0.84 | 0.82 | 0.82 | 96 |
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+ | **Weighted avg** | 0.97 | 0.94 | 0.94 | 96 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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