Update README.md

README.md

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 ---
 license: apache-2.0
 ---
+
+---
+license: cc-by-4.0
+language:
+- es
+tags:
+- casimedicos
+- explainability
+- medical exams
+- medical question answering
+- extractive question answering
+- squad
+- multilinguality
+- LLMs
+- LLM
+pretty_name: mdeberta-expl-extraction-multi
+task_categories:
+- question-answering
+size_categories:
+- 1K<n<10K
+---
+
+<p align="center">
+    <br>
+    <img src="http://www.ixa.eus/sites/default/files/anitdote.png" style="height: 200px;">
+    <br>
+
+# mdeberta-v3-base finetuned for Explanatory Argument Extraction
+
+We finetuned mdeberta-v3-base on a **novel extractive task** which consists of **identifying the explanation of the correct answer written by
+medical doctors in medical exams**.
+
+The training data is based on [Antidote CasiMedicos](https://huggingface.co/datasets/HiTZ/casimedicos-squad) for EN,ES,FR,IT languages.
+
+The data source consists of Resident Medical Intern or Médico Interno Residente (MIR) exams, originally
+created by [CasiMedicos](https://www.casimedicos.com), a Spanish community of medical professionals who collaboratively, voluntarily, 
+and free of charge, publishes written explanations about the possible answers included in the MIR exams. The aim is to generate a resource that
+helps future medical doctors to study towards the MIR examinations. The commented MIR exams, including the explanations, are published in the [CasiMedicos 
+Project MIR 2.0 website](https://www.casimedicos.com/mir-2-0/).
+
+We have extracted, clean, structure and annotated the available data so that each document in **casimedicos-squad** includes the clinical case, the correct answer, 
+the multiple-choice questions and the commented exam written by native Spanish medical doctors. The comments have been annotated with the span in the text that
+corresponds to the explanation of the correct answer (see example below).
+
+<table style="width:33%">
+    <tr>
+         <th>casimedicos-squad splits</th>
+     <tr>
+         <td>train</td>
+         <td>404</td>
+     </tr>
+     <tr>
+         <td>validation</td>
+         <td>56</td>
+     </tr>
+     <tr>
+         <td>test</td>
+         <td>119</td>
+     </tr>
+ </table>
+
+
+
+
+## Example
+
+<p align="center">
+<img src="https://github.com/ixa-ehu/antidote-casimedicos/blob/main/casimedicos-exp.png?raw=true" style="height: 650px;">
+</p>
+
+The example above shows a document in CasiMedicos containing the textual content, including Clinical Case (C), Question (Q), Possible Answers (P), 
+and Explanation (E). Furthermore, for **casimedicos-squad** we annotated the span in the explanation (E) that corresponds to the correct answer (A).
+
+ The process of manually annotating the corpus consisted of specifying where the explanations of the correct answers begin and end. 
+ In order to obtain grammatically complete correct answer explanations, annotating full sentences or subordinate clauses was preferred over
+ shorter spans. 
+
+## Data Explanation
+
+The dataset is structured as a list of documents ("paragraphs") where each of them include:
+
+- **context**: the explanation (E) in the document
+- **qas**: list of possible answers and questions. This element contains:
+    - **answers**: an answer which corresponds to the explanation of the correct answer (A)
+    - **question**: the clinical case (C) and question (Q)
+    - **id**: unique identifier for the document
+
+## Citation
+
+
+If you use this data please **cite the following paper**:
+
+```bibtex
+@misc{goenaga2023explanatory,
+      title={Explanatory Argument Extraction of Correct Answers in Resident Medical Exams}, 
+      author={Iakes Goenaga and Aitziber Atutxa and Koldo Gojenola and Maite Oronoz and Rodrigo Agerri},
+      year={2023},
+      eprint={2312.00567},
+      archivePrefix={arXiv}
+}
+```
+
+**Contact**: [Iakes Goenaga](http://www.hitz.eus/es/node/65) and [Rodrigo Agerri](https://ragerri.github.io/)
+HiTZ Center - Ixa, University of the Basque Country UPV/EHU
+
+
+
+
+### Model Description
+
+
+- 📖 **Paper**:[Explanatory Argument Extraction of Correct Answers in Resident Medical Exams](https://arxiv.org/abs/2312.00567)
+- 💻 **Github Repo** (Data and Code): [https://github.com/ixa-ehu/antidote-casimedicos](https://github.com/ixa-ehu/antidote-casimedicos)
+- 🌐 **Project Website**: [https://univ-cotedazur.eu/antidote](https://univ-cotedazur.eu/antidote)
+- **Funding**: CHIST-ERA XAI 2019 call. Antidote (PCI2020-120717-2) funded by MCIN/AEI /10.13039/501100011033 and by European Union NextGenerationEU/PRTR
+- **Language(s) (NLP):** EN,ES,FR,IT
+- **License:** Apache License 2
+- **Finetuned from model:** microsoft/mdeberta-v3-base
+
+## 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]
+
+
+#### 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:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]