Update README.md

README.md

@@ -2,6 +2,25 @@
 license: mit
 tags:
 - generated_from_trainer
+- financial-sentiment-analysis
+- sentiment-analysis
+- sentence_50agree
+- financial
+- stocks
+- sentiment
+datasets:
+- financial_phrasebank
+- Kaggle Self label
+- nickmuchi/financial-classification
+widget:
+- text: "The USD rallied by 3% last night as the Fed hiked interest rates"
+  example_title: "Bullish Sentiment"
+- text: "Covid-19 cases have been increasing over the past few months impacting earnings for global firms"
+  example_title: "Bearish Sentiment"
+- text: "the USD has been trending lower"
+  example_title: "Mildly Bearish Sentiment"
+- text: "The USD rallied by 3% last night as the Fed hiked interest rates however, higher interest rates will increase mortgage costs for homeowners"
+  example_title: "Neutral"
 metrics:
 - accuracy
 - f1
@@ -12,12 +31,10 @@ model-index:
   results: []
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
 # deberta-v3-base-finetuned-finance-text-classification
 
-This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the sentence_50Agree [financial-phrasebank + Kaggle Dataset](https://huggingface.co/datasets/nickmuchi/financial-classification), a dataset consisting of 4840 Financial News categorised by sentiment (negative, neutral, positive). The Kaggle dataset includes Covid-19 sentiment data and can be found here: [sentiment-classification-selflabel-dataset](https://www.kaggle.com/percyzheng/sentiment-classification-selflabel-dataset).
+
 It achieves the following results on the evaluation set:
 - Loss: 0.7687
 - Accuracy: 0.8913