Update README.md

README.md

@@ -10,6 +10,10 @@ This is the smallest GPT-2 model (124m) from OpenAi finetuned on approximately 2
 
 The model was trained with a learning rate of 1e-4, with a warmup of 1024 steps, then decaying to 0. There were 4400 total steps during training at a batch size of 512 examples with a context length of 1024. The batch size and context length are the same as the pre-training of GPT2 itself. Training took a total of 1.18e+18 FLOs over the course of 79.32 hours locally with a 12gb RTX3060. Final train loss was 2.73.
 
+The resulting model achieves a puplexity of 339.38, making it competative with Cerebras-590m with only 21% of the parameters, and much better than the original GPT-2 which scores 491.57!
+
+(metric explanation here: https://twitter.com/aicrumb/status/1650350363898265601 , tldr it's a joke, kind of)
+
 *(from GPT-2 model card)*
 
 ### Model description