Which accuracy do I need to reach for a decent agent?

[PeterLeon]

I ve trained my model by using 200gb of driving data and inception_v3 model on same street with same weather conditions and 8.000 epochs with 300kb batches per epoch and learning rate of 0.000000001.
Accuracy is somewhat about 0.2(smoothed).
But when I test it out it keeps pressing WD with a verage plus of 0.3 of probability.

My question, how much data and which acc. do I need for a decent agent?

Tensorboard:
http://honesthome.ddns.net/s.png

Example Output [W, WA, WD, S, SA, SD, A, D]:
[ 0.1167456 0.16700381 0.27807635 0.05266069 0.08322734 0.1091948
0.11513347 0.07795788]
0.278076350689
forward_right
[ 0.11684461 0.16718809 0.27833453 0.0525772 0.08328342 0.1088759
0.11493194 0.07796425]
0.278334528208
forward_right
[ 0.11666095 0.16800123 0.27791589 0.05253068 0.08310306 0.10876592
0.11503578 0.07798637]
0.277915894985
forward_right
[ 0.116884 0.16714898 0.2784971 0.05255117 0.08334375 0.10875834
0.11481125 0.0780055 ]
0.278497099876
forward_right
[ 0.11672532 0.16719386 0.27897081 0.05252673 0.08339871 0.10860606
0.11471127 0.07786718]
0.278970807791
forward_right
[ 0.11685108 0.16760175 0.27800107 0.05256343 0.08338011 0.10876746
0.11482292 0.07801216]

[germanmarky]

0.2 accuracy (20%) is quite low, and with 8 different predictions, even a random prediction is 0.125 (12.5%). If you trained your model at a learning rate of 1e-9, that is VERY low, you shouldn't start it any lower than 1e-5, I would use 1e-3 for one epoch, see how the accruacy/loss were progressing, and adjust down accordingly for later epochs.