hi
i used deepspeech and did the training to the end and get the wer result
i saved the the run log in a text file like below
i need to plot the train loss and dev loss , how i can do this with my thext file that i saved after i finished my run
?
Please don’t post images.
-
Either write them manually into Excel or something.
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Use Tensorboard for the TF logs.
thanx
next time i will care about image
?but how i can use Tensorboard
is there a command
please guied me in steps
Please take the time to read the links we provide …
which link?
link of policy?
How to ask questions here, that you just clicked. It talks about searching before asking. Please do so and ask if anything is still unclear.
help yourself:
$ git grep -i tensorboard
training/deepspeech_training/util/flags.py: f.DEFINE_string('summary_dir', '', 'target directory for TensorBoard summaries - defaults to directory "deepspeech/summaries" within user\'s data home specified by the XDG Base Directory Specification')
ok i try it manaually in Excel
but because # of steps in valiation ( i have 11 steps )not equal to number of steps in training
(i have 190 steps)
i cant draw well in Excel
so can i try the last step only from each epoch for training (step # 190 ) and valiadation ( step # 11) to be able to draw them in Excel
?
is this right
like this:
epoch dev_loss train_loss
281.13 287.76 1
and complete like this for all the epochs
Please read more about deep learning in a book, website, … This is totally normal, you have more training than validation material. And read about overfitting.
ok that’s normal and i know this
i just ask to draw in excel
i want to draw the train loss and validiation loss in the same graph
so it’s right to take the last step in each epoch for train and validation
this my question
I have no idea what you mean. At the end of each epoch you get a loss for train and dev. Those two values should be almost the same. If not, you got other problems. I therefore see no problem at all in drawing them in one graph.
Please post all your losses as a list if you need more help.
i want to take the loss value of step 189 in train for each epoch and the dev loss in step 11 in each epoch
then draw with these values for each epochs in excel
…
my loss
| I | STARTING | |||||
|---|---|---|---|---|---|---|
| Epoch | 0 | Training | Steps: | 0 | Loss: | 0 |
| Epoch | 0 | Training | Steps: | 1 | Loss: | 321.413727 |
| Epoch | 0 | Training | Steps: | 2 | Loss: | 274.250114 |
| Epoch | 0 | Training | Steps: | 3 | Loss: | 228.34049 |
| Epoch | 0 | Training | Steps: | 4 | Loss: | 214.206993 |
| Epoch | 0 | Training | Steps: | 5 | Loss: | 208.963528 |
| Epoch | 0 | Training | Steps: | 6 | Loss: | 196.165075 |
| Epoch | 0 | Training | Steps: | 7 | Loss: | 188.474908 |
| Epoch | 0 | Training | Steps: | 8 | Loss: | 184.570635 |
| Epoch | 0 | Training | Steps: | 9 | Loss: | 180.292511 |
| Epoch | 0 | Training | Steps: | 10 | Loss: | 176.097978 |
| Epoch | 0 | Training | Steps: | 11 | Loss: | 172.2453 |
| Epoch | 0 | Training | Steps: | 12 | Loss: | 172.627689 |
| Epoch | 0 | Training | Steps: | 13 | Loss: | 171.214926 |
| Epoch | 0 | Training | Steps: | 14 | Loss: | 169.700439 |
| Epoch | 0 | Training | Steps: | 15 | Loss: | 167.763425 |
| Epoch | 0 | Training | Steps: | 16 | Loss: | 168.02154 |
| Epoch | 0 | Training | Steps: | 17 | Loss: | 166.868439 |
| Epoch | 0 | Training | Steps: | 18 | Loss: | 166.02983 |
| Epoch | 0 | Training | Steps: | 19 | Loss: | 165.570595 |
| Epoch | 0 | Training | Steps: | 20 | Loss: | 166.347802 |
| Epoch | 0 | Training | Steps: | 21 | Loss: | 165.931118 |
| Epoch | 0 | Training | Steps: | 22 | Loss: | 166.198478 |
| Epoch | 0 | Training | Steps: | 23 | Loss: | 165.929836 |
| Epoch | 0 | Training | Steps: | 24 | Loss: | 166.504939 |
| Epoch | 0 | Training | Steps: | 25 | Loss: | 166.984387 |
| Epoch | 0 | Training | Steps: | 26 | Loss: | 167.228056 |
| Epoch | 0 | Training | Steps: | 27 | Loss: | 167.864794 |
| Epoch | 0 | Training | Steps: | 28 | Loss: | 167.890928 |
| Epoch | 0 | Training | Steps: | 29 | Loss: | 168.119032 |
| Epoch | 0 | Training | Steps: | 30 | Loss: | 168.249385 |
| Epoch | 0 | Training | Steps: | 31 | Loss: | 168.954264 |
| Epoch | 0 | Training | Steps: | 32 | Loss: | 169.742381 |
| Epoch | 0 | Training | Steps: | 33 | Loss: | 171.271692 |
| Epoch | 0 | Training | Steps: | 34 | Loss: | 171.657708 |
| Epoch | 0 | Training | Steps: | 35 | Loss: | 172.394131 |
| Epoch | 0 | Training | Steps: | 36 | Loss: | 173.379232 |
| Epoch | 0 | Training | Steps: | 37 | Loss: | 173.88664 |
| Epoch | 0 | Training | Steps: | 38 | Loss: | 174.682091 |
| Epoch | 0 | Training | Steps: | 39 | Loss: | 175.717712 |
| Epoch | 0 | Training | Steps: | 40 | Loss: | 176.827482 |
| Epoch | 0 | Training | Steps: | 41 | Loss: | 177.491054 |
| Epoch | 0 | Training | Steps: | 42 | Loss: | 178.152844 |
| Epoch | 0 | Training | Steps: | 43 | Loss: | 180.227668 |
| Epoch | 0 | Training | Steps: | 44 | Loss: | 180.763937 |
| Epoch | 0 | Training | Steps: | 45 | Loss: | 181.684411 |
| Epoch | 0 | Training | Steps: | 46 | Loss: | 182.522912 |
| Epoch | 0 | Training | Steps: | 47 | Loss: | 182.713796 |
| Epoch | 0 | Training | Steps: | 48 | Loss: | 183.554088 |
| Epoch | 0 | Training | Steps: | 49 | Loss: | 184.815238 |
| Epoch | 0 | Training | Steps: | 50 | Loss: | 185.667325 |
| Epoch | 0 | Training | Steps: | 51 | Loss: | 186.256064 |
| Epoch | 0 | Training | Steps: | 52 | Loss: | 187.207739 |
| Epoch | 0 | Training | Steps: | 53 | Loss: | 187.980089 |
| Epoch | 0 | Training | Steps: | 54 | Loss: | 189.253979 |
| Epoch | 0 | Training | Steps: | 55 | Loss: | 189.837776 |
| Epoch | 0 | Training | Steps: | 56 | Loss: | 190.47533 |
| Epoch | 0 | Training | Steps: | 57 | Loss: | 191.604262 |
| Epoch | 0 | Training | Steps: | 58 | Loss: | 192.498031 |
| Epoch | 0 | Training | Steps: | 59 | Loss: | 193.232261 |
| Epoch | 0 | Training | Steps: | 60 | Loss: | 193.997013 |
| Epoch | 0 | Training | Steps: | 61 | Loss: | 195.137949 |
| Epoch | 0 | Training | Steps: | 62 | Loss: | 195.657982 |
| Epoch | 0 | Training | Steps: | 63 | Loss: | 196.571748 |
| Epoch | 0 | Training | Steps: | 64 | Loss: | 197.321499 |
| Epoch | 0 | Training | Steps: | 65 | Loss: | 198.016298 |
| Epoch | 0 | Training | Steps: | 66 | Loss: | 199.045432 |
| Epoch | 0 | Training | Steps: | 67 | Loss: | 199.629425 |
| Epoch | 0 | Training | Steps: | 68 | Loss: | 200.057538 |
| Epoch | 0 | Training | Steps: | 69 | Loss: | 200.296114 |
| Epoch | 0 | Training | Steps: | 70 | Loss: | 201.072869 |
| Epoch | 0 | Training | Steps: | 71 | Loss: | 202.161726 |
| Epoch | 0 | Training | Steps: | 72 | Loss: | 203.318399 |
| Epoch | 0 | Training | Steps: | 73 | Loss: | 203.950737 |
| Epoch | 0 | Training | Steps: | 74 | Loss: | 204.757916 |
| Epoch | 0 | Training | Steps: | 75 | Loss: | 205.641084 |
| Epoch | 0 | Training | Steps: | 76 | Loss: | 206.276845 |
| Epoch | 0 | Training | Steps: | 77 | Loss: | 206.804886 |
| Epoch | 0 | Training | Steps: | 78 | Loss: | 207.704927 |
| Epoch | 0 | Training | Steps: | 79 | Loss: | 208.565614 |
| Epoch | 0 | Training | Steps: | 80 | Loss: | 209.202545 |
| Epoch | 0 | Training | Steps: | 81 | Loss: | 209.647832 |
| Epoch | 0 | Training | Steps: | 82 | Loss: | 210.59161 |
| Epoch | 0 | Training | Steps: | 83 | Loss: | 211.53423 |
| Epoch | 0 | Training | Steps: | 84 | Loss: | 212.042662 |
| Epoch | 0 | Training | Steps: | 85 | Loss: | 212.994805 |
| Epoch | 0 | Training | Steps: | 86 | Loss: | 213.555281 |
| Epoch | 0 | Training | Steps: | 87 | Loss: | 214.340172 |
| Epoch | 0 | Training | Steps: | 88 | Loss: | 214.901834 |
| Epoch | 0 | Training | Steps: | 89 | Loss: | 215.380082 |
| Epoch | 0 | Training | Steps: | 90 | Loss: | 216.007 |
| Epoch | 0 | Training | Steps: | 91 | Loss: | 216.689602 |
| Epoch | 0 | Training | Steps: | 92 | Loss: | 217.729824 |
| Epoch | 0 | Training | Steps: | 93 | Loss: | 218.747647 |
| Epoch | 0 | Training | Steps: | 94 | Loss: | 219.555463 |
| Epoch | 0 | Training | Steps: | 95 | Loss: | 220.19487 |
| Epoch | 0 | Training | Steps: | 96 | Loss: | 220.981938 |
| Epoch | 0 | Training | Steps: | 97 | Loss: | 221.674749 |
| Epoch | 0 | Training | Steps: | 98 | Loss: | 222.2959 |
| Epoch | 0 | Training | Steps: | 99 | Loss: | 222.708379 |
| Epoch | 0 | Training | Steps: | 100 | Loss: | 223.552934 |
| Epoch | 0 | Training | Steps: | 101 | Loss: | 224.617271 |
| Epoch | 0 | Training | Steps: | 102 | Loss: | 225.368554 |
| Epoch | 0 | Training | Steps: | 103 | Loss: | 225.779093 |
| Epoch | 0 | Training | Steps: | 104 | Loss: | 226.112573 |
| Epoch | 0 | Training | Steps: | 105 | Loss: | 227.088227 |
| Epoch | 0 | Training | Steps: | 106 | Loss: | 228.005511 |
| Epoch | 0 | Training | Steps: | 107 | Loss: | 228.628655 |
| Epoch | 0 | Training | Steps: | 108 | Loss: | 228.989545 |
| Epoch | 0 | Training | Steps: | 109 | Loss: | 229.576564 |
| Epoch | 0 | Training | Steps: | 110 | Loss: | 230.278917 |
| Epoch | 0 | Training | Steps: | 111 | Loss: | 230.986006 |
| Epoch | 0 | Training | Steps: | 112 | Loss: | 232.104331 |
| Epoch | 0 | Training | Steps: | 113 | Loss: | 232.767508 |
| Epoch | 0 | Training | Steps: | 114 | Loss: | 233.622867 |
| Epoch | 0 | Training | Steps: | 115 | Loss: | 234.132088 |
| Epoch | 0 | Training | Steps: | 116 | Loss: | 234.709264 |
| Epoch | 0 | Training | Steps: | 117 | Loss: | 235.154217 |
| Epoch | 0 | Training | Steps: | 118 | Loss: | 235.8605 |
| Epoch | 0 | Training | Steps: | 119 | Loss: | 236.522191 |
| Epoch | 0 | Training | Steps: | 120 | Loss: | 237.046127 |
| Epoch | 0 | Training | Steps: | 121 | Loss: | 237.819763 |
| Epoch | 0 | Training | Steps: | 122 | Loss: | 238.326473 |
| Epoch | 0 | Training | Steps: | 123 | Loss: | 238.806476 |
| Epoch | 0 | Training | Steps: | 124 | Loss: | 239.872133 |
| Epoch | 0 | Training | Steps: | 125 | Loss: | 240.310268 |
| Epoch | 0 | Training | Steps: | 126 | Loss: | 241.310326 |
| Epoch | 0 | Training | Steps: | 127 | Loss: | 241.970896 |
| Epoch | 0 | Training | Steps: | 128 | Loss: | 242.311593 |
| Epoch | 0 | Training | Steps: | 129 | Loss: | 242.914341 |
| Epoch | 0 | Training | Steps: | 130 | Loss: | 243.5522 |
| Epoch | 0 | Training | Steps: | 131 | Loss: | 244.06975 |
| Epoch | 0 | Training | Steps: | 132 | Loss: | 244.686553 |
| Epoch | 0 | Training | Steps: | 133 | Loss: | 245.319197 |
| Epoch | 0 | Training | Steps: | 134 | Loss: | 246.175137 |
| Epoch | 0 | Training | Steps: | 135 | Loss: | 246.983793 |
| Epoch | 0 | Training | Steps: | 136 | Loss: | 247.68559 |
| Epoch | 0 | Training | Steps: | 137 | Loss: | 248.654289 |
| Epoch | 0 | Training | Steps: | 138 | Loss: | 248.971996 |
| Epoch | 0 | Training | Steps: | 139 | Loss: | 249.722913 |
| Epoch | 0 | Training | Steps: | 140 | Loss: | 250.562798 |
| Epoch | 0 | Training | Steps: | 141 | Loss: | 251.229299 |
| Epoch | 0 | Training | Steps: | 142 | Loss: | 252.088471 |
| Epoch | 0 | Training | Steps: | 143 | Loss: | 252.475349 |
| Epoch | 0 | Training | Steps: | 144 | Loss: | 253.000376 |
| Epoch | 0 | Training | Steps: | 145 | Loss: | 253.820551 |
| Epoch | 0 | Training | Steps: | 146 | Loss: | 254.543652 |
| Epoch | 0 | Training | Steps: | 147 | Loss: | 255.558965 |
| Epoch | 0 | Training | Steps: | 148 | Loss: | 256.409514 |
| Epoch | 0 | Training | Steps: | 149 | Loss: | 256.8467 |
| Epoch | 0 | Training | Steps: | 150 | Loss: | 257.505127 |
| Epoch | 0 | Training | Steps: | 151 | Loss: | 258.138038 |
| Epoch | 0 | Training | Steps: | 152 | Loss: | 258.769062 |
| Epoch | 0 | Training | Steps: | 153 | Loss: | 259.715915 |
| Epoch | 0 | Training | Steps: | 154 | Loss: | 260.289005 |
| Epoch | 0 | Training | Steps: | 155 | Loss: | 261.089299 |
| Epoch | 0 | Training | Steps: | 156 | Loss: | 261.823436 |
| Epoch | 0 | Training | Steps: | 157 | Loss: | 262.680497 |
| Epoch | 0 | Training | Steps: | 158 | Loss: | 263.436903 |
| Epoch | 0 | Training | Steps: | 159 | Loss: | 264.142053 |
| Epoch | 0 | Training | Steps: | 160 | Loss: | 264.542494 |
| Epoch | 0 | Training | Steps: | 161 | Loss: | 265.214357 |
| Epoch | 0 | Training | Steps: | 162 | Loss: | 265.863622 |
| Epoch | 0 | Training | Steps: | 163 | Loss: | 266.352972 |
| Epoch | 0 | Training | Steps: | 164 | Loss: | 266.940236 |
| Epoch | 0 | Training | Steps: | 165 | Loss: | 267.257496 |
| Epoch | 0 | Training | Steps: | 166 | Loss: | 267.829717 |
| Epoch | 0 | Training | Steps: | 167 | Loss: | 268.251283 |
| Epoch | 0 | Training | Steps: | 168 | Loss: | 268.727684 |
| Epoch | 0 | Training | Steps: | 169 | Loss: | 269.405363 |
| Epoch | 0 | Training | Steps: | 170 | Loss: | 270.175061 |
| Epoch | 0 | Training | Steps: | 171 | Loss: | 270.617402 |
| Epoch | 0 | Training | Steps: | 172 | Loss: | 271.275992 |
| Epoch | 0 | Training | Steps: | 173 | Loss: | 271.883822 |
| Epoch | 0 | Training | Steps: | 174 | Loss: | 272.443641 |
| Epoch | 0 | Training | Steps: | 175 | Loss: | 272.816036 |
| Epoch | 0 | Training | Steps: | 176 | Loss: | 273.475419 |
| Epoch | 0 | Training | Steps: | 177 | Loss: | 273.821474 |
| Epoch | 0 | Training | Steps: | 178 | Loss: | 274.248569 |
| Epoch | 0 | Training | Steps: | 179 | Loss: | 274.570182 |
| Epoch | 0 | Training | Steps: | 180 | Loss: | 275.009499 |
| Epoch | 0 | Training | Steps: | 181 | Loss: | 275.850796 |
| Epoch | 0 | Training | Steps: | 182 | Loss: | 276.580054 |
| Epoch | 0 | Training | Steps: | 183 | Loss: | 276.538092 |
| Epoch | 0 | Training | Steps: | 184 | Loss: | 276.722951 |
| Epoch | 0 | Training | Steps: | 185 | Loss: | 277.158755 |
| Epoch | 0 | Training | Steps: | 186 | Loss: | 277.767248 |
| Epoch | 0 | Training | Steps: | 187 | Loss: | 278.458153 |
| Epoch | 0 | Training | Steps: | 188 | Loss: | 279.663077 |
| Epoch | 0 | Training | Steps: | 189 | Loss: | 281.13091 |
| Epoch | 0 | Training | Steps: | 189 | Loss: | 281.13091 |
| Epoch | 0 | Validation | Steps: | 0 | Loss: | 0 |
| Epoch | 0 | Validation | Steps: | 1 | Loss: | 121.765717 |
| Epoch | 0 | Validation | Steps: | 2 | Loss: | 145.615875 |
| Epoch | 0 | Validation | Steps: | 3 | Loss: | 168.556376 |
| Epoch | 0 | Validation | Steps: | 4 | Loss: | 188.541576 |
| Epoch | 0 | Validation | Steps: | 5 | Loss: | 203.227158 |
| Epoch | 0 | Validation | Steps: | 6 | Loss: | 215.930758 |
| Epoch | 0 | Validation | Steps: | 7 | Loss: | 231.736989 |
| Epoch | 0 | Validation | Steps: | 8 | Loss: | 245.324053 |
| Epoch | 0 | Validation | Steps: | 9 | Loss: | 260.627809 |
| Epoch | 0 | Validation | Steps: | 10 | Loss: | 273.784914 |
| Epoch | 0 | Validation | Steps: | 11 | Loss: | 287.678149 |
| Epoch | 0 | Validation | Steps: | 11 | Loss: | 287.678149 |
| I | Saved | best | to: | /media/suhad/Backup/Female/Female_Model/check/best_dev-189 | ||
| Epoch | 1 | Training | Steps: | 0 | Loss: | 0 |
| Epoch | 1 | Training | Steps: | 1 | Loss: | 93.885338 |
| Epoch | 1 | Training | Steps: | 2 | Loss: | 105.46907 |
| Epoch | 1 | Training | Steps: | 3 | Loss: | 107.689229 |
| Epoch | 1 | Training | Steps: | 4 | Loss: | 108.453352 |
| Epoch | 1 | Training | Steps: | 5 | Loss: | 110.235846 |
| Epoch | 1 | Training | Steps: | 6 | Loss: | 110.105855 |
| Epoch | 1 | Training | Steps: | 7 | Loss: | 111.845933 |
| Epoch | 1 | Training | Steps: | 8 | Loss: | 113.319835 |
| Epoch | 1 | Training | Steps: | 9 | Loss: | 113.653712 |
| Epoch | 1 | Training | Steps: | 10 | Loss: | 114.393449 |
| Epoch | 1 | Training | Steps: | 11 | Loss: | 114.510318 |
| Epoch | 1 | Training | Steps: | 12 | Loss: | 117.430259 |
| Epoch | 1 | Training | Steps: | 13 | Loss: | 118.39091 |
| Epoch | 1 | Training | Steps: | 14 | Loss: | 119.480721 |
| Epoch | 1 | Training | Steps: | 15 | Loss: | 119.997499 |
| Epoch | 1 | Training | Steps: | 16 | Loss: | 122.1861 |
| Epoch | 1 | Training | Steps: | 17 | Loss: | 122.610662 |
| Epoch | 1 | Training | Steps: | 18 | Loss: | 123.250743 |
| Epoch | 1 | Training | Steps: | 19 | Loss: | 124.257875 |
| Epoch | 1 | Training | Steps: | 20 | Loss: | 126.287601 |
| Epoch | 1 | Training | Steps: | 21 | Loss: | 127.017939 |
| Epoch | 1 | Training | Steps: | 22 | Loss: | 128.295131 |
| Epoch | 1 | Training | Steps: | 23 | Loss: | 128.994421 |
| Epoch | 1 | Training | Steps: | 24 | Loss: | 130.484928 |
| Epoch | 1 | Training | Steps: | 25 | Loss: | 131.705511 |
| Epoch | 1 | Training | Steps: | 26 | Loss: | 132.590434 |
| Epoch | 1 | Training | Steps: | 27 | Loss: | 133.795081 |
| Epoch | 1 | Training | Steps: | 28 | Loss: | 134.48608 |
| Epoch | 1 | Training | Steps: | 29 | Loss: | 135.280229 |
| Epoch | 1 | Training | Steps: | 30 | Loss: | 135.958721 |
| Epoch | 1 | Training | Steps: | 31 | Loss: | 137.018428 |
| Epoch | 1 | Training | Steps: | 32 | Loss: | 138.153359 |
| Epoch | 1 | Training | Steps: | 33 | Loss: | 140.187495 |
| Epoch | 1 | Training | Steps: | 34 | Loss: | 140.887085 |
| Epoch | 1 | Training | Steps: | 35 | Loss: | 141.804683 |
| Epoch | 1 | Training | Steps: | 36 | Loss: | 143.052915 |
| Epoch | 1 | Training | Steps: | 37 | Loss: | 143.802977 |
| Epoch | 1 | Training | Steps: | 38 | Loss: | 144.887164 |
| Epoch | 1 | Training | Steps: | 39 | Loss: | 146.170584 |
| Epoch | 1 | Training | Steps: | 40 | Loss: | 147.38827 |
| Epoch | 1 | Training | Steps: | 41 | Loss: | 148.224903 |
| Epoch | 1 | Training | Steps: | 42 | Loss: | 149.100671 |
| Epoch | 1 | Training | Steps: | 43 | Loss: | 151.412516 |
| Epoch | 1 | Training | Steps: | 44 | Loss: | 151.983169 |
| Epoch | 1 | Training | Steps: | 45 | Loss: | 152.98084 |
| Epoch | 1 | Training | Steps: | 46 | Loss: | 153.905083 |
| Epoch | 1 | Training | Steps: | 47 | Loss: | 154.180877 |
| Epoch | 1 | Training | Steps: | 48 | Loss: | 155.030491 |
| Epoch | 1 | Training | Steps: | 49 | Loss: | 156.210837 |
| Epoch | 1 | Training | Steps: | 50 | Loss: | 157.13859 |
| Epoch | 1 | Training | Steps: | 51 | Loss: | 157.853126 |
| Epoch | 1 | Training | Steps: | 52 | Loss: | 158.792322 |
| Epoch | 1 | Training | Steps: | 53 | Loss: | 159.630391 |
| Epoch | 1 | Training | Steps: | 54 | Loss: | 160.958859 |
| Epoch | 1 | Training | Steps: | 55 | Loss: | 161.536199 |
| Epoch | 1 | Training | Steps: | 56 | Loss: | 162.181854 |
| Epoch | 1 | Training | Steps: | 57 | Loss: | 163.210989 |
| Epoch | 1 | Training | Steps: | 58 | Loss: | 164.012153 |
| Epoch | 1 | Training | Steps: | 59 | Loss: | 164.711438 |
| Epoch | 1 | Training | Steps: | 60 | Loss: | 165.398431 |
| Epoch | 1 | Training | Steps: | 61 | Loss: | 166.497156 |
| Epoch | 1 | Training | Steps: | 62 | Loss: | 166.949616 |
| Epoch | 1 | Training | Steps: | 63 | Loss: | 167.791386 |
| Epoch | 1 | Training | Steps: | 64 | Loss: | 168.424391 |
| Epoch | 1 | Training | Steps: | 65 | Loss: | 169.032524 |
| Epoch | 1 | Training | Steps: | 66 | Loss: | 169.969604 |
| Epoch | 1 | Training | Steps: | 67 | Loss: | 170.476334 |
| Epoch | 1 | Training | Steps: | 68 | Loss: | 170.872876 |
| Epoch | 1 | Training | Steps: | 69 | Loss: | 171.016887 |
| Epoch | 1 | Training | Steps: | 70 | Loss: | 171.71477 |
| Epoch | 1 | Training | Steps: | 71 | Loss: | 172.731642 |
| Epoch | 1 | Training | Steps: | 72 | Loss: | 173.824774 |
| Epoch | 1 | Training | Steps: | 73 | Loss: | 174.48142 |
| Epoch | 1 | Training | Steps: | 74 | Loss: | 175.198805 |
| Epoch | 1 | Training | Steps: | 75 | Loss: | 175.902579 |
| Epoch | 1 | Training | Steps: | 76 | Loss: | 176.417507 |
| Epoch | 1 | Training | Steps: | 77 | Loss: | 176.848157 |
| Epoch | 1 | Training | Steps: | 78 | Loss: | 177.638632 |
| Epoch | 1 | Training | Steps: | 79 | Loss: | 178.379598 |
| Epoch | 1 | Training | Steps: | 80 | Loss: | 178.950134 |
| Epoch | 1 | Training | Steps: | 81 | Loss: | 179.240046 |
| Epoch | 1 | Training | Steps: | 82 | Loss: | 180.042554 |
| Epoch | 1 | Training | Steps: | 83 | Loss: | 180.740483 |
| Epoch | 1 | Training | Steps: | 84 | Loss: | 181.106959 |
| Epoch | 1 | Training | Steps: | 85 | Loss: | 181.832513 |
| Epoch | 1 | Training | Steps: | 86 | Loss: | 182.245962 |
| Epoch | 1 | Training | Steps: | 87 | Loss: | 182.959026 |
| Epoch | 1 | Training | Steps: | 88 | Loss: | 183.329708 |
| Epoch | 1 | Training | Steps: | 89 | Loss: | 183.716621 |
| Epoch | 1 | Training | Steps: | 90 | Loss: | 184.30786 |
| Epoch | 1 | Training | Steps: | 91 | Loss: | 184.786527 |
| Epoch | 1 | Training | Steps: | 92 | Loss: | 185.534353 |
| Epoch | 1 | Training | Steps: | 93 | Loss: | 186.373447 |
| Epoch | 1 | Training | Steps: | 94 | Loss: | 187.028669 |
| Epoch | 1 | Training | Steps: | 95 | Loss: | 187.432783 |
| Epoch | 1 | Training | Steps: | 96 | Loss: | 188.049592 |
| Epoch | 1 | Training | Steps: | 97 | Loss: | 188.550222 |
| Epoch | 1 | Training | Steps: | 98 | Loss: | 188.9246 |
| Epoch | 1 | Training | Steps: | 99 | Loss: | 189.203066 |
| Epoch | 1 | Training | Steps: | 100 | Loss: | 189.891383 |
| Epoch | 1 | Training | Steps: | 101 | Loss: | 190.601805 |
| Epoch | 1 | Training | Steps: | 102 | Loss: | 191.126005 |
| Epoch | 1 | Training | Steps: | 103 | Loss: | 191.316733 |
| Epoch | 1 | Training | Steps: | 104 | Loss: | 191.414879 |
| Epoch | 1 | Training | Steps: | 105 | Loss: | 192.088687 |
| Epoch | 1 | Training | Steps: | 106 | Loss: | 192.7903 |
| Epoch | 1 | Training | Steps: | 107 | Loss: | 193.233029 |
| Epoch | 1 | Training | Steps: | 108 | Loss: | 193.340453 |
| Epoch | 1 | Training | Steps: | 109 | Loss: | 193.653095 |
| Epoch | 1 | Training | Steps: | 110 | Loss: | 194.087426 |
| Epoch | 1 | Training | Steps: | 111 | Loss: | 194.498201 |
| Epoch | 1 | Training | Steps: | 112 | Loss: | 195.194921 |
| Epoch | 1 | Training | Steps: | 113 | Loss: | 195.575221 |
| Epoch | 1 | Training | Steps: | 114 | Loss: | 196.097759 |
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| Epoch | 1 | Training | Steps: | 189 | Loss: | 221.144483 |
| Epoch | 1 | Validation | Steps: | 0 | Loss: | 0 |
| Epoch | 1 | Validation | Steps: | 1 | Loss: | 113.519081 |
| Epoch | 00:00.0 | Validation | Steps: | 2 | Loss: | 129.466358 |
| Epoch | 1 | Validation | Steps: | 3 | Loss: | 146.661507 |
| Epoch | 1 | Validation | Steps: | 4 | Loss: | 162.482805 |
| Epoch | 1 | Validation | Steps: | 5 | Loss: | 173.632558 |
| Epoch | 1 | Validation | Steps: | 6 | Loss: | 182.39616 |
| Epoch | 1 | Validation | Steps: | 7 | Loss: | 195.113823 |
| Epoch | 1 | Validation | Steps: | 8 | Loss: | 206.321427 |
| Epoch | 1 | Validation | Steps: | 9 | Loss: | 218.254684 |
| Epoch | 1 | Validation | Steps: | 10 | Loss: | 228.056385 |
| Epoch | 1 | Validation | Steps: | 11 | Loss: | 238.205143 |
| Epoch | 1 | Validation | Steps: | 11 | Loss: | 238.205143 |
| WARNING:tensorflow:From | /home/suhad/anaconda3/envs/tf_gpu/lib/python3.6/site-packages/tensorflow_core/python/training/saver.py:963: | (from | be | removed | a | future |
| Instructions | for | |||||
| Use | standard | APIs | prefix. | |||
| W1012 | 25:02.3 | deprecation.py:323] | is | deprecated | will | be |
| Instructions | for | |||||
| Use | standard | APIs | prefix. | |||
| I | Saved | best | to: | /media/suhad/Backup/Female/Female_Model/check/best_dev-378 | ||
| Epoch | 2 | Training | Steps: | 0 | Loss: | 0 |
| Epoch | 2 | Training | Steps: | 1 | Loss: | 84.537727 |
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| Epoch | 2 | Training | Steps: | 124 | Loss: | 142.372535 |
| Epoch | 2 | Training | Steps: | 125 | Loss: | 142.469672 |
| Epoch | 2 | Training | Steps: | 126 | Loss: | 143.115664 |
| Epoch | 2 | Training | Steps: | 127 | Loss: | 143.392886 |
| Epoch | 2 | Training | Steps: | 128 | Loss: | 143.439242 |
| Epoch | 2 | Training | Steps: | 129 | Loss: | 143.637522 |
| Epoch | 2 | Training | Steps: | 130 | Loss: | 143.877761 |
| Epoch | 2 | Training | Steps: | 131 | Loss: | 144.155935 |
| Epoch | 2 | Training | Steps: | 132 | Loss: | 144.415318 |
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| Epoch | 2 | Training | Steps: | 134 | Loss: | 145.158993 |
| Epoch | 2 | Training | Steps: | 135 | Loss: | 145.647907 |
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| Epoch | 2 | Training | Steps: | 147 | Loss: | 149.962235 |
| Epoch | 2 | Training | Steps: | 148 | Loss: | 150.536769 |
| Epoch | 2 | Training | Steps: | 149 | Loss: | 150.774858 |
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| Epoch | 2 | Training | Steps: | 153 | Loss: | 152.304684 |
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| Epoch | 2 | Training | Steps: | 155 | Loss: | 152.957764 |
| Epoch | 2 | Training | Steps: | 156 | Loss: | 153.407811 |
| Epoch | 2 | Training | Steps: | 157 | Loss: | 153.818284 |
| Epoch | 2 | Training | Steps: | 158 | Loss: | 154.39387 |
| Epoch | 2 | Training | Steps: | 159 | Loss: | 154.839447 |
| Epoch | 2 | Training | Steps: | 160 | Loss: | 155.019265 |
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| Epoch | 2 | Training | Steps: | 163 | Loss: | 156.052133 |
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| Epoch | 2 | Training | Steps: | 166 | Loss: | 156.700117 |
| Epoch | 2 | Training | Steps: | 167 | Loss: | 156.962358 |
| Epoch | 2 | Training | Steps: | 168 | Loss: | 157.137838 |
| Epoch | 2 | Training | Steps: | 169 | Loss: | 157.562598 |
| Epoch | 2 | Training | Steps: | 170 | Loss: | 157.906284 |
| Epoch | 2 | Training | Steps: | 171 | Loss: | 158.107699 |
| Epoch | 2 | Training | Steps: | 172 | Loss: | 158.489592 |
| Epoch | 2 | Training | Steps: | 173 | Loss: | 158.703795 |
| Epoch | 2 | Training | Steps: | 174 | Loss: | 158.95709 |
| Epoch | 2 | Training | Steps: | 175 | Loss: | 159.012622 |
| Epoch | 2 | Training | Steps: | 176 | Loss: | 159.322996 |
| Epoch | 2 | Training | Steps: | 177 | Loss: | 159.424613 |
| Epoch | 2 | Training | Steps: | 178 | Loss: | 159.502893 |
| Epoch | 2 | Training | Steps: | 179 | Loss: | 159.515867 |
| Epoch | 2 | Training | Steps: | 180 | Loss: | 159.730942 |
| Epoch | 2 | Training | Steps: | 181 | Loss: | 160.017307 |
| Epoch | 2 | Training | Steps: | 182 | Loss: | 160.260526 |
| Epoch | 2 | Training | Steps: | 183 | Loss: | 160.241578 |
| Epoch | 2 | Training | Steps: | 184 | Loss: | 160.376199 |
| Epoch | 2 | Training | Steps: | 185 | Loss: | 160.738875 |
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| Epoch | 2 | Training | Steps: | 187 | Loss: | 161.737454 |
| Epoch | 2 | Training | Steps: | 188 | Loss: | 162.518582 |
| Epoch | 2 | Training | Steps: | 189 | Loss: | 163.543491 |
| Epoch | 2 | Training | Steps: | 189 | Loss: | 163.543491 |
| Epoch | 2 | Validation | Steps: | 0 | Loss: | 0 |
| Epoch | 2 | Validation | Steps: | 1 | Loss: | 102.870201 |
| Epoch | 2 | Validation | Steps: | 2 | Loss: | 115.629292 |
| Epoch | 2 | Validation | Steps: | 3 | Loss: | 129.61867 |
| Epoch | 2 | Validation | Steps: | 4 | Loss: | 143.766481 |
| Epoch | 2 | Validation | Steps: | 5 | Loss: | 153.634288 |
| Epoch | 2 | Validation | Steps: | 6 | Loss: | 161.297087 |
| Epoch | 2 | Validation | Steps: | 7 | Loss: | 172.887999 |
| Epoch | 2 | Validation | Steps: | 8 | Loss: | 182.471589 |
| Epoch | 2 | Validation | Steps: | 9 | Loss: | 192.893213 |
| Epoch | 2 | Validation | Steps: | 10 | Loss: | 201.555518 |
| Epoch | 2 | Validation | Steps: | 11 | Loss: | 210.967455 |
| Epoch | 2 | Validation | Steps: | 11 | Loss: | 210.967455 |
| I | Saved | best | to: | /media/suhad/Backup/Female/Female_Model/check/best_dev-567 | ||
| Epoch | 3 | Training | Steps: | 0 | Loss: | 0 |
| Epoch | 3 | Training | Steps: | 1 | Loss: | 72.287598 |
| Epoch | 3 | Training | Steps: | 2 | Loss: | 75.019886 |
| Epoch | 3 | Training | Steps: | 3 | Loss: | 73.277911 |
| Epoch | 3 |
i list only the first
because the it excced the max number that allowed here in the post
Just take the last value of train and dev for each epoch as you described above.
@othiele
and this is will be ok and correct
?
or take the avgerage of all the steps for each epoch in train and dev then draw
?
which’s is the correct
?
@lissyx
hi
iam sorry for annoy you
but if have any answer about my question
i want to take the loss value of the last step in train for each epoch and the dev loss value in the step in each epoch
then draw with these values for each epochs in excel
or
take the avgerage of all the steps for each epoch in train and dev then draw
which is correct
?
…