Update README.md

README.md

@@ -10,5 +10,9 @@ GPTDynamics is a dataset for training and evaluating GPT simulators with trainin
 
 ## Dataset Structure
 - **id**: ID of test examples
-- **trajectory**: A list of training status items for training the GPT. Each item includes the current training step, the corresponding training sample, and the test metrics for the test sample with ID *id*.
-## Data Instances
+- **trajectory**: A list of training status items for GPT training. Each item includes the current training step, the corresponding training sample, and the test metrics for the test sample with ID *id*.
+## Data Instances
+Here is an example of GPTDynamics:
+```
+{"id": 200, "loss_trajectory": [{"step": 1, "loss": 2.1776978969573975}, {"step": 2, "loss": 1.9405722618103027}, {"step": 3, "loss": 1.7367844581604004}, {"step": 4, "loss": 1.7367844581604004}, {"step": 5, "loss": 1.5723190307617188}, {"step": 6, "loss": 1.4200186729431152}, {"step": 7, "loss": 1.3043007850646973}, {"step": 8, "loss": 1.2168896198272705}, {"step": 9, "loss": 1.1534075736999512}, {"step": 10, "loss": 1.1152348518371582}, {"step": 11, "loss": 1.1152348518371582}, {"step": 12, "loss": 1.0790379047393799}, {"step": 13, "loss": 1.0651202201843262}, {"step": 14, "loss": 1.0498850345611572}, {"step": 15, "loss": 1.031670331954956}, {"step": 16, "loss": 1.0191452503204346}, {"step": 17, "loss": 1.0147688388824463}, {"step": 18, "loss": 0.9998137950897217}, {"step": 19, "loss": 0.9855930209159851}, {"step": 20, "loss": 0.9674589037895203}, {"step": 21, "loss": 0.9639376401901245}, {"step": 22, "loss": 0.9576956033706665}, {"step": 23, "loss": 0.9551132917404175}, {"step": 24, "loss": 0.9648815393447876}, {"step": 25, "loss": 0.9736171364784241}, {"step": 26, "loss": 0.9851577281951904}, {"step": 27, "loss": 0.9893707036972046}, {"step": 28, "loss": 1.0030837059020996}, {"step": 29, "loss": 1.0139732360839844}, {"step": 30, "loss": 1.0163781642913818}, {"step": 31, "loss": 1.0070099830627441}, {"step": 32, "loss": 0.9952836036682129}, {"step": 33, "loss": 0.9842988848686218}, {"step": 34, "loss": 0.9693409204483032}, {"step": 35, "loss": 0.9520652890205383}, {"step": 36, "loss": 0.9321508407592773}, {"step": 37, "loss": 0.9054916501045227}, {"step": 38, "loss": 0.8903782367706299}, {"step": 39, "loss": 0.8781676292419434}, {"step": 40, "loss": 0.8616900444030762}, {"step": 41, "loss": 0.8523870706558228}, {"step": 42, "loss": 0.8555602431297302}, {"step": 43, "loss": 0.857650876045227}, {"step": 44, "loss": 0.8613216876983643}, {"step": 45, "loss": 0.862149715423584}, {"step": 46, "loss": 0.8526755571365356}, {"step": 47, "loss": 0.8449978828430176}, {"step": 48, "loss": 0.8408513069152832}, {"step": 49, "loss": 0.836147665977478}, {"step": 50, "loss": 0.8282585740089417}, {"step": 51, "loss": 0.8207768201828003}, {"step": 52, "loss": 0.8117837905883789}, {"step": 53, "loss": 0.8007177710533142}, {"step": 54, "loss": 0.7916263937950134}, {"step": 55, "loss": 0.7800232172012329}, {"step": 56, "loss": 0.7684219479560852}, {"step": 57, "loss": 0.7614703178405762}, {"step": 58, "loss": 0.7508001327514648}, {"step": 59, "loss": 0.741269588470459}, {"step": 60, "loss": 0.7335830330848694}, {"step": 61, "loss": 0.7259370684623718}, {"step": 62, "loss": 0.7219422459602356}, {"step": 63, "loss": 0.7146060466766357}, {"step": 64, "loss": 0.7088412642478943}, {"step": 65, "loss": 0.7015798091888428}, {"step": 66, "loss": 0.6983332633972168}, {"step": 67, "loss": 0.6971897482872009}, {"step": 68, "loss": 0.6952411532402039}, {"step": 69, "loss": 0.6954054236412048}, {"step": 70, "loss": 0.69813472032547}, {"step": 71, "loss": 0.7001814842224121}, {"step": 72, "loss": 0.6996586322784424}, {"step": 73, "loss": 0.6953248977661133}, {"step": 74, "loss": 0.6917775273323059}, {"step": 75, "loss": 0.6852239370346069}, {"step": 76, "loss": 0.6780304908752441}, {"step": 77, "loss": 0.6724499464035034}, {"step": 78, "loss": 0.6652747392654419}, {"step": 79, "loss": 0.6599810719490051}, {"step": 80, "loss": 0.6562151908874512}, {"step": 81, "loss": 0.6603475213050842}, {"step": 82, "loss": 0.6595749258995056}, {"step": 83, "loss": 0.6532007455825806}, {"step": 84, "loss": 0.6475570797920227}, {"step": 85, "loss": 0.6428706049919128}, {"step": 86, "loss": 0.638140082359314}, {"step": 87, "loss": 0.6333405375480652}, {"step": 88, "loss": 0.6285641193389893}, {"step": 89, "loss": 0.6250292658805847}, {"step": 90, "loss": 0.6216303110122681}, {"step": 91, "loss": 0.6190891861915588}, {"step": 92, "loss": 0.6162238717079163}, {"step": 93, "loss": 0.6136907935142517}, {"step": 94, "loss": 0.6119751930236816}, {"step": 95, "loss": 0.6114301085472107}, {"step": 96, "loss": 0.6112507581710815}]}
+```