Update README.md

README.md

@@ -33,7 +33,7 @@ The model has underwent a post-training process that incorporates both **supervi
 ### Chat Format
 
 Given the nature of the training data, the Phi-1.5 Instruct model is best suited for prompts using the chat format as follows. 
-You can provide the prompt as a question with a generic template as follow:
+You can provide the prompt as a question with a generic template as follows:
 ```markdown
 <|im_start|>system
 You are a helpful assistant.<|im_end|>
@@ -99,7 +99,7 @@ Note: If you want to use flash attention, call _AutoModelForCausalLM.from_pretra
 
 ## Benchmarks
 
-This model outperforms HuggingFace's SmolLM-1.7B-Instruct and the TinyLlama-1.1B-Chat-v1.0 models on IFEval and GSM8K benchmarks. These benchmarks were run using EleutherAI's [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness)
+This model outperforms HuggingFace's SmolLM-1.7B-Instruct and the TinyLlama-1.1B-Chat-v1.0 models on **all 5** of the following benchmarks. These benchmarks were run using EleutherAI's [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness)
 
 - **IFEval (Instruction Following Evaluation)**: IFEval is a fairly interesting dataset that tests the capability of models to clearly follow explicit instructions, such as “include keyword x” or “use format y”. The models are tested on their ability to strictly follow formatting instructions rather than the actual contents generated, allowing strict and rigorous metrics to be used.
 - **GSM8k (5-shot)**: diverse grade school math word problems to measure a model's ability to solve multi-step mathematical reasoning problems.