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README.md

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 # Finetuned destilBERT model for stock news classification
 
-This is a HuggingFace model that uses BERT (Bidirectional Encoder Representations from Transformers) to perform text classification tasks. It was fine-tuned on 50.000 stock news articles using the HuggingFace adapter from Kern AI refinery.
-BERT is a state-of-the-art pre-trained language model that can encode both the left and right context of a word in a sentence, allowing it to capture complex semantic and syntactic information.
-
+This destilbert model was fine-tuned on 50.000 stock news articles using the HuggingFace adapter from Kern AI refinery. The articles consisted of the headlines plus abstract of the article.
+For the finetuning, a single NVidia K80 was used for about four hours. 
+DistilBERT is a smaller, faster and lighter version of BERT. It was trained by distilling BERT base and has 40% less parameters than bert-base-uncased. 
+It runs 60% faster while preserving over 95% of BERT’s performances as measured on the GLUE language understanding benchmark 1. 
+DistilBERT does not have token-type embeddings, pooler and retains only half of the layers from Google’s BERT 2
 ## Features
 
 - The model can handle various text classification tasks, especially when it comes to stock and finance news sentiment classification.
-- The model can accept either single sentences or sentence pairs as input, and output a probability distribution over the predefined classes.
-- The model can be fine-tuned on custom datasets and labels using the HuggingFace Trainer API or the PyTorch Lightning integration.
-- The model is currently supported by the PyTorch framework and can be easily deployed on various platforms using the HuggingFace Pipeline API or the ONNX Runtime.
+- The output of the model are the three classes "positive", "neutral" and "negative" plus the models respective confidence score of the class. 
+- The model was fine-tuned on a custom datasets that was curated by Kern AI and labeled in our tool refinery.
+- The model is currently supported by the PyTorch framework and can be easily deployed on various platforms using the HuggingFace Pipeline API.
 
 ## Usage