Change Readme (add Bert)

.gitignore

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README.md

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 | -e,--epochs           | number of epochs                                                                |
 | -d,--dimension        | size of the ngram embeddings                                                    |
 | --admin_code_1        | (Optional) If you wish to train the network on a specific region             |
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+
+# New model based on BERT embeddings
+
+In the recent years, BERT architecture proposed by Google researches enables to outperform state-of-art methods for differents tasks in NLP (POS, NER, Classification). To verify if BERT embeddings would permit to increase the performance of our approach, we code a script to use bert with our data. In our previous model, the model returned two values each on between [0,1]. Using Bert, the task has shifted to classification (softmax) where each class correspond to a cell on the glob. We use the hierarchical projection model : Healpix. Other projections model like S2geometry can be considered : https://s2geometry.io/about/overview.
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+In order, to run this model training, run the `bert.py` script :
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+    python3 bert.py <train_dataset> <test_dataset>
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+The train and test dataset are table data composed of two columns: sentence and label.
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