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The app can be viewed here: [Financial Dashboard](https://awinml-financial-market-intelligence-app-q6lj0g.streamlit.app/)
+## **Data**
+To extract the text from the SEC filing, the SEC’s ExtractorAPI was used. The API can extract any text section from 10-Q, 10-K, and 8-K SEC filings, and returns the extracted content in cleaned and standardized text or HTML format.
+The twelve companies for which the data has been collected as listed below organized by sector:
+1. Pharmaceutical:
+Abbvie, Pfizer, Merck
+2. Technology:
+Alphabet, Meta, Microsoft
+3. Retail:
+Costco
+4. Oil and Natural Gas:
+Chevron
+5. Food and Beverages:
+Coca Cola, Pepsico
+
+The can be viewed as
+
+
+## **Sentiment Analysis**
+A local cross validation split was created by randomly sampling rows from the records of 12 companies across sectors like Technology, Finance, Retail and Pharma.
+
+ A sample 10k report for Meta can be viewed here
+
+The RoBERTa, FinBERT and DistilBERT models were fine-tuned for sentiment analysis. The best results were obtained using the fine-tuned **DistilBERT** model. It achieved an Accuracy of 91.11% and an ROC-AUC Score of 0.972.
+
+
+| Model | Accuracy | F1 | AUC |
+| ----- | ------ | -------- | ------------------ |
+| Roberta | 0.662 | 0.656 | 0.628 |
+| FinBERT | 0.746 | 0.682 | 0.721 |
+| DistilBERT | 0.911 | 0.914 | 0.972 |
+
+## **Summarization**
+
+For the summarization task, the data of Pfizer, Costco and Meta was labeled and used. A local cross validation split was created by randomly sampling rows from the records of these companies.
+Text summarization was carried out using these three transformers models:
+
+The T5, DistilPEGASUS and DistilBART models were fine-tuned for summarization. The best results were obtained using the fine-tuned **DistilBART** model. It achieved an ROUGE-L Score of 67.7%.
+
+
+| Model | ROUGUE-1 | ROUGUE-2 | ROUGUE-L | ROUGUE-LSUM
+| ----- | ------ | -------- | ------------------ | ------------------|
+| T5| 32.22 | 28.5 | 31.5| 31.5 | 31.5 |
+| DistilPEGASUS | 48.32 | 34.48 |43.51| 31.50 |
+| DistilBART | 72.28 | 61.15 | 67.70 | 71 |
+
+
+
+## **Identifying Important Keywords**
+
+RAKE NLTK was used to identify important keywords from the generated summaries.
+
+
+