Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Q/Mean,Q/Stdev,Q/Max,Q/Min
1,0.0,1.0,1117.0,1117.0,1117.0,1117.0,1.0,,,0.0,,,,,,,,,,,,,,,,,,,
2,205.0,0.0,1937.0,1937.0,820.0,1937.0,0.9991882000000176,-21.0,-21.0,0.0,,,,0.014763841533212831,0.013646937264058223,0.06725655496120453,2.0758947357535362e-05,0.00010000000000000002,1.3552527156068802e-20,0.0001,0.0001,0.17952479999999998,0.13626544,0.9860897,0.0053134440000000005,,,,
3,413.0,0.0,2768.0,2768.0,831.0,2768.0,0.9983655100000356,-21.0,-21.0,0.0,,,,0.012111850191891229,0.013912744765592264,0.08914861083030699,1.7985148588195443e-05,0.00010000000000000003,2.7105054312137605e-20,0.0001,0.0001,0.057201855,0.04205291,0.26596984,0.0031672046,-0.04456665,0.009031756,-0.031443898,-0.059377108
4,667.0,0.0,3783.0,3783.0,1015.0,3783.0,0.9973606600000572,-20.0,-20.0,0.0,,,,0.013269104183936587,0.013449185914245043,0.07771021127700806,1.3188657248974778e-05,0.00010000000000000002,1.3552527156068802e-20,0.0001,0.0001,0.098453455,0.109315164,0.9814589,0.0024465397,-0.008853295,0.009689603,0.0003574537,-0.028319128
5,867.0,0.0,4585.0,4585.0,802.0,4585.0,0.9965666800000744,-21.0,-21.0,0.0,,,,0.01383970570535894,0.013677503957050816,0.0817062109708786,5.106279422761872e-05,0.00010000000000000002,1.3552527156068802e-20,0.0001,0.0001,0.108334474,0.0749226,0.40531653,0.006287096,-0.018026425,0.047121227,0.035217006,-0.070681214