Update README.md

README.md

@@ -9,15 +9,11 @@ datasets:
 
 # Description
 
-This is a basic implementation of the multilingual model ["ixambert-base-cased"](https://huggingface.co/ixa-ehu/ixambert-base-cased), fine-tuned on SQuAD version 1.1, that is able to answer basic factual questions in English, Spanish and Basque. It extracts the span of text in which the answer is found.
-
+This is a basic implementation of the multilingual model ["ixambert-base-cased"](https://huggingface.co/ixa-ehu/ixambert-base-cased), fine-tuned on SQuAD version 1.1, that is able to answer basic factual questions in English, Spanish and Basque. 
 
 ### Outputs
 
-The model predicts a span of text from the context and a score for the probability for that span to be the correct answer:
-
-* Toxic: the tweet has at least some degree of toxicity.
-* Very Toxic: the tweet has a strong degree of toxicity.
+The model predicts a span of text from the context and a score for the probability for that span to be the correct answer.
 
 
 ### How to use
@@ -33,11 +29,11 @@ The model can be used directly with a *question-answering* pipeline:
 {'score': 0.9667195081710815, 'start': 101, 'end': 105, 'answer': '1820'}
 ```
 
-%### Training procedure
-%The pre-trained model was fine-tuned for question answering using the following hyperparameters, which were selected from a validation set:
-
-%* Batch size = 32
-%* Learning rate = 2e-5
-%* Epochs = 3
+### Training procedure
+The pre-trained model was fine-tuned for question answering using the following hyperparameters:
 
-%The optimizer used was AdamW and the loss optimized was binary cross-entropy with class weights proportional to the class imbalance.
+* Batch size = na
+* Learning rate = na
+* Epochs = 3
+* Optimizer = AdamW
+* Loss = na