Update README.md

README.md

@@ -59,25 +59,17 @@ We DO NOT recommend to fine-tune this model. It is already meant to be a downstr
 
 This model can be directly used for classifying dermatological text data in Spanish EHRs.
 
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-### Downstream Use [optional]
+### Downstream Use
 The model can be integrated into healthcare applications for automatic classification of dermatological conditions from patient records.
 
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-[More Information Needed]
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 ### Out-of-Scope Use
 
 The model is not suitable for non-medical text classification tasks or for texts in languages other than Spanish.
 
-[More Information Needed]
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 ## Bias, Risks, and Limitations
 
 This model is fine-tuned on a specific dataset and may not generalize well to other types of medical texts or conditions. Users should be cautious of biases in the training data that could affect the model's performance.
 
-[More Information Needed]
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 ### Recommendations
 
 <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
@@ -103,14 +95,11 @@ outputs = model(input_ids, attention_mask=attention_mask)
 ```
 
 
-[More Information Needed]
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 ## Training Details
 
 ### Training Data
 
 The model was fine-tuned on the DermatES dataset from Fundación CTIC, which contains Spanish dermatological EHRs.
-[More Information Needed]
 
 ### Training Procedure
 In order to reproduce the experiment it is ESSENTIAL to respect the order of prediction of the three ontology-base features. More details in the original paper of *Dermat*
@@ -147,7 +136,7 @@ predicted_diseases = cascade(inputs,information_list,model,tokenizer)
 ```
 
 
-#### Preprocessing [optional]
+#### Preprocessing
 
 Lowercased, anonymized and accents removed texts
 
@@ -156,14 +145,12 @@ Lowercased, anonymized and accents removed texts
 
 - **Training regime:** fp32
 
-#### Speeds, Sizes, Times [optional]
+#### Speeds, Sizes, Times
 
     Epochs: 7
     Batch size: 64
     Learning rate: 0.0001
 
-[More Information Needed]
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 ## Evaluation
 
 
@@ -175,8 +162,6 @@ Lowercased, anonymized and accents removed texts
 
 The evaluation was performed on 0.2 of the [DermatES](https://huggingface.co/datasets/fundacionctic/DermatES) dataset.
 
-[More Information Needed]
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 #### Factors
 
 <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
@@ -230,14 +215,12 @@ Two NVIDIA GPUs were used for the fine-tuning process.
 
 The fine-tuning was performed using the 🤗 Transformers library.
 
-## Citation [optional]
+## Citation
 
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 
 **BibTeX:** Coming soon 
 
-[More Information Needed]
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 **APA:**
 
 [More Information Needed]
@@ -250,10 +233,11 @@ The fine-tuning was performed using the 🤗 Transformers library.
 
 [More Information Needed]
 
-## Model Card Authors [optional]
+## Model Card Authors
 
 Leon-Paul Schaub Torre, Pelayo Quiros and Helena Garcia-Mieres
 
 ## Model Card Contact
 
-leon.schaub@fundacionctic.org
+leon.schaub@fundacionctic.org
+pelayo.quiros@fundacionctic.org