Update README.md

README.md

@@ -16,4 +16,51 @@ configs:
   data_files:
   - split: test
     path: data/test-*
+license: mit
+task_categories:
+- text-generation
+language:
+- en
+tags:
+- finance
+- financial sentiment
+size_categories:
+- n<1K
 ---
+Here's a README for your HuggingFace dataset designed for identifying the financial sentiment of event transcript segments:
+
+---
+
+# Financial Sentiment Analysis Dataset
+
+## Description
+
+This dataset focuses on the sentiment analysis of earnings call transcript segments. It provides pre-segmented extracts from earnings calls, transcribed by Aiera, paired with sentiment labels. Each segment in the `transcript` column is annotated with a sentiment label (`sentiment`), which can be "positive", "negative", or "neutral". This dataset is intended for training and evaluating models on their ability to discern the underlying sentiment in financial communications.
+
+## Dataset Structure
+
+### Columns
+
+- `transcript`: A segment of the earnings call transcript.
+- `sentiment`: The sentiment label for the transcript segment, with possible values being "positive", "negative", or "neutral".
+
+### Data Format
+
+The dataset is structured in a tabular format, with each row representing a unique segment of an earnings call transcript alongside its corresponding sentiment label.
+
+## Use Cases
+
+This dataset is particularly suited for applications such as:
+- Training machine learning models to perform sentiment analysis specifically in financial contexts.
+- Developing algorithms to assist financial analysts and investors by providing quick sentiment assessments of earnings calls.
+- Enhancing natural language processing systems used in finance for better understanding of market mood and company performance.
+
+## Accessing the Dataset
+
+To access this dataset, you can load it using the HuggingFace Datasets library with the following Python code:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Aiera/aiera-transcript-sentiment")
+```