Update README.md

README.md

@@ -53,10 +53,9 @@ Introduction to Finetuning LLMs course - Learning
 ### Downstream Use [optional]
 
 This model is designed for tasks requiring improved alignment with human preferences, such as:
-Chatbots
-Question-answering systems
-General text generation with enhanced preference alignment<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
+- Chatbots
+- Question-answering systems
+- General text generation with enhanced preference alignment<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
 
 ### Out-of-Scope Use
 
@@ -166,12 +165,6 @@ Training Data
 - Content: Prompts, chosen answers, and rejected answers
 
 
-
-|  Tasks  |Version|Filter|n-shot| Metric |   |Value |   |Stderr|
-|---------|------:|------|-----:|--------|---|-----:|---|-----:|
-|hellaswag|      1|none  |     0|acc     |↑  |0.4516|±  |0.0050|
-|         |       |none  |     0|acc_norm|↑  |0.6139|±  |0.0049|
-
 Task: HellaSwag
 - This is a benchmark task designed to evaluate a model's commonsense reasoning and ability to complete scenarios logically.
 - No specific filtering was applied to the test set.
@@ -190,8 +183,6 @@ Interpretation:
 
 <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
 
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
 - **Hardware Type:** A100
 - **Hours used:** No comment
 - **Cloud Provider:** Google Collab
@@ -203,7 +194,7 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 Hardware: A100 GPU
 
 
-## Model Card Authors [optional]
+## Model Card Author
 
 Ruth Shacterman