Update README.md

README.md

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 ---
-library_name: transformers
-tags: []
----
-
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## 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. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[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]
-
+license: cc-by-nc-4.0
+language:
+- hu
+metrics:
+- accuracy
+- f1
+model-index:
+- name: Hun_RoBERTa_large_Plain
+  results:
+  - task:
+      type: text-classification
+    metrics:
+      - type: accuracy
+        value: 0.79
+      - type: f1
+        value: 0.79
+widget:
+- text: "A tanúsítvány meghatározott adatainak a 2008/118/EK irányelv IV. fejezete szerinti szállításához szükséges adminisztratív okmányban..."
+  example_title: "Incomprehensible"
+- text: "Az AEO-engedély birtokosainak listáján – keresésre – megjelenő információk: az engedélyes neve, az engedélyt kibocsátó ország..."
+  example_title: "Comprehensible"
 
-#### 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]
-
-<!-- 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]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-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).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [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]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
+---
 
-**APA:**
+## Model description
 
-[More Information Needed]
+Cased fine-tuned XLM-RoBERTa-large model for Hungarian, trained to classify sentences based on their plain language comprehensibility.
 
-## Glossary [optional]
+## Intended uses & limitations
 
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+The model is designed to classify sentences as either "comprehensible" or "not comprehensible" (according to Plain Language guidelines):
+* **Label_0** - "comprehensible"
+* **Label_1** - "not comprehensible"
 
-[More Information Needed]
+## Training
 
-## More Information [optional]
+Fine-tuned version of the original `xlm-roberta-large` model, trained on a dataset of Hungarian legal and administrative texts.
 
-[More Information Needed]
+## Eval results
 
-## Model Card Authors [optional]
+| Class | Precision | Recall | F-Score |
+| ----- | --------- | ------ | ------- |
+| **Comprehensible / Label_0** | **0.76** | **0.86** | **0.81** |
+| **Not comprehensible / Label_1** | **0.83** | **0.72** | **0.77** |
+| **accuracy** | | | **0.79** |
+| **macro avg** | **0.80** | **0.79** | **0.79** |
+| **weighted avg** | **0.79** | **0.79** | **0.79** |
 
-[More Information Needed]
+## Usage
 
-## Model Card Contact
+```py
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
-[More Information Needed]
+tokenizer = AutoTokenizer.from_pretrained("uvegesistvan/Hun_RoBERTa_large_Plain")
+model = AutoModelForSequenceClassification.from_pretrained("uvegesistvan/Hun_RoBERTa_large_Plain")
+```