adding the model evaluation metrics document

Author: CaesarGhazi

0_domain_study/model_evaluation_metrics.md

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+# Model Testing Metrics
+
+|Skill Type (Task)|What It Tests|Example Dataset|Metric to Measure Accuracy|
+|-----------------|-------------|---------------|--------------------------|
+|Reasoning / Logic|Mathematical reasoning|GSM8K|(correct answers / total)|
+|Commonsense QA|Everyday reasoning and knowledge|PIQA, BoolQ|Accuracy|
+|Summarization|condense information|CNN/DailyMail, XSum|ROUGE-L, BERTScore|
+|Code Generation|Logical structure|HumanEval-lite, MBPP|Pass@k|
+
+## Datasets
+
+### GSM8K(Grade School Math 8K)
+
+It is a dataset of 8.5K high quality linguistically diverse
+grade school math word problems. The dataset was created to support the task
+of question answering on basic mathematical problems that require multi-step
+reasoning.
+
+### BoolQ
+
+It is a question answering dataset for yes/no questions containing
+15942 examples. These questions are naturally occurring ---they are
+generated in unprompted and unconstrained settings.
+
+### PIQA
+
+This dataset introduces the task of physical commonsense reasoning and a
+corresponding benchmark dataset Physical Interaction: Question Answering
+or PIQA.
+
+### Extreme Summarization (XSum) Dataset
+
+There are three features:
+document: Input news article.
+summary: One sentence summary of the article.
+id: BBC ID of the article.
+
+### The CNN / DailyMail Dataset
+
+It is an English-language dataset containing just over
+300k unique news articles as written by journalists at CNN and the Daily Mail.
+he current version supports both extractive and abstractive summarization.
+The HumanEval dataset released by OpenAI includes 164 programming problems
+with a function sig- nature, docstring, body, and several unit tests.
+They were handwritten to ensure not to be included in the training
+set of code generation models.
+
+### MBPP
+
+The benchmark consists of around 1,000 crowd-sourced Python programming
+problems, designed to be solvable by entry level programmers, covering
+programming fundamentals, standard library functionality, and so on.
+Each problem consists of a task description,code solution and 3 automated
+test cases.
+
+## Metrics
+
+### Pass@1
+
+The percentage of problems for which the model’s first generated solution
+passes all tests.
+
+### BERTScore
+
+It measures how similar two pieces of text are in meaning, not just in word
+overlap. It uses BERT embeddings (or similar transformer embeddings) to
+compare the semantic content of the generated text and the reference text.
+
+### ROUGE, or Recall-Oriented Understudy for Gisting Evaluation
+
+It is a set of metrics and a software package used for evaluating automatic
+summarization and machine translation software in natural language processing.
+The metrics compare an automatically produced summary or translation against
+a reference or a set of references (human-produced) summary or translation.