From 4cc55348c8dbb1902a1246fba66237d5c59f0349 Mon Sep 17 00:00:00 2001 From: InigoGutierrez Date: Fri, 1 Jul 2022 15:40:57 +0200 Subject: Finished writing documentation. --- doc/listings/convModel.txt | 23 +++++++++++++++++++++++ doc/listings/convTraining.txt | 40 ++++++++++++++++++++++++++++++++++++++++ doc/listings/denseModel.txt | 17 +++++++++++++++++ doc/listings/denseTraining.txt | 40 ++++++++++++++++++++++++++++++++++++++++ doc/listings/trainCommand.sh | 1 + 5 files changed, 121 insertions(+) create mode 100644 doc/listings/convModel.txt create mode 100644 doc/listings/convTraining.txt create mode 100644 doc/listings/denseModel.txt create mode 100644 doc/listings/denseTraining.txt create mode 100644 doc/listings/trainCommand.sh (limited to 'doc/listings') diff --git a/doc/listings/convModel.txt b/doc/listings/convModel.txt new file mode 100644 index 0000000..5c90975 --- /dev/null +++ b/doc/listings/convModel.txt @@ -0,0 +1,23 @@ +Model: "sequential" +_________________________________________________________________ + Layer (type) Output Shape Param # +================================================================= + conv2d (Conv2D) (None, 9, 9, 32) 608 + + max_pooling2d (MaxPooling2D (None, 4, 4, 32) 0 + ) + + conv2d_1 (Conv2D) (None, 4, 4, 64) 18496 + + max_pooling2d_1 (MaxPooling (None, 2, 2, 64) 0 + 2D) + + flatten (Flatten) (None, 256) 0 + + dense (Dense) (None, 82) 21074 + +================================================================= +Total params: 40,178 +Trainable params: 40,178 +Non-trainable params: 0 +_________________________________________________________________ diff --git a/doc/listings/convTraining.txt b/doc/listings/convTraining.txt new file mode 100644 index 0000000..6108abc --- /dev/null +++ b/doc/listings/convTraining.txt @@ -0,0 +1,40 @@ +Epoch 1/20 +39501/39501 - 279s - loss: 3.7391 - accuracy: 0.1064 - val_loss: 3.1316 - val_accuracy: 0.2023 - 279s/epoch - 7ms/step +Epoch 2/20 +39501/39501 - 241s - loss: 2.6512 - accuracy: 0.3046 - val_loss: 2.0729 - val_accuracy: 0.4484 - 241s/epoch - 6ms/step +Epoch 3/20 +39501/39501 - 214s - loss: 1.6459 - accuracy: 0.6014 - val_loss: 1.2040 - val_accuracy: 0.7143 - 214s/epoch - 5ms/step +Epoch 4/20 +39501/39501 - 228s - loss: 0.9016 - accuracy: 0.8417 - val_loss: 0.6430 - val_accuracy: 0.8735 - 228s/epoch - 6ms/step +Epoch 5/20 +39501/39501 - 230s - loss: 0.4704 - accuracy: 0.9380 - val_loss: 0.3520 - val_accuracy: 0.9378 - 230s/epoch - 6ms/step +Epoch 6/20 +39501/39501 - 222s - loss: 0.2735 - accuracy: 0.9520 - val_loss: 0.2329 - val_accuracy: 0.9549 - 222s/epoch - 6ms/step +Epoch 7/20 +39501/39501 - 215s - loss: 0.2117 - accuracy: 0.9495 - val_loss: 0.1837 - val_accuracy: 0.9583 - 215s/epoch - 5ms/step +Epoch 8/20 +39501/39501 - 215s - loss: 0.1797 - accuracy: 0.9533 - val_loss: 0.1787 - val_accuracy: 0.9556 - 215s/epoch - 5ms/step +Epoch 9/20 +39501/39501 - 225s - loss: 0.1607 - accuracy: 0.9553 - val_loss: 0.1952 - val_accuracy: 0.9446 - 225s/epoch - 6ms/step +Epoch 10/20 +39501/39501 - 249s - loss: 0.1486 - accuracy: 0.9572 - val_loss: 0.1544 - val_accuracy: 0.9597 - 249s/epoch - 6ms/step +Epoch 11/20 +39501/39501 - 208s - loss: 0.1380 - accuracy: 0.9586 - val_loss: 0.1467 - val_accuracy: 0.9651 - 208s/epoch - 5ms/step +Epoch 12/20 +39501/39501 - 210s - loss: 0.1321 - accuracy: 0.9592 - val_loss: 0.1313 - val_accuracy: 0.9665 - 210s/epoch - 5ms/step +Epoch 13/20 +39501/39501 - 204s - loss: 0.1276 - accuracy: 0.9598 - val_loss: 0.1282 - val_accuracy: 0.9665 - 204s/epoch - 5ms/step +Epoch 14/20 +39501/39501 - 193s - loss: 0.1222 - accuracy: 0.9604 - val_loss: 0.1174 - val_accuracy: 0.9686 - 193s/epoch - 5ms/step +Epoch 15/20 +39501/39501 - 183s - loss: 0.1182 - accuracy: 0.9607 - val_loss: 0.1747 - val_accuracy: 0.9433 - 183s/epoch - 5ms/step +Epoch 16/20 +39501/39501 - 166s - loss: 0.1147 - accuracy: 0.9611 - val_loss: 0.1186 - val_accuracy: 0.9679 - 166s/epoch - 4ms/step +Epoch 17/20 +39501/39501 - 163s - loss: 0.1119 - accuracy: 0.9616 - val_loss: 0.1112 - val_accuracy: 0.9699 - 163s/epoch - 4ms/step +Epoch 18/20 +39501/39501 - 168s - loss: 0.1095 - accuracy: 0.9618 - val_loss: 0.1020 - val_accuracy: 0.9706 - 168s/epoch - 4ms/step +Epoch 19/20 +39501/39501 - 161s - loss: 0.1072 - accuracy: 0.9625 - val_loss: 0.1058 - val_accuracy: 0.9699 - 161s/epoch - 4ms/step +Epoch 20/20 +39501/39501 - 173s - loss: 0.1052 - accuracy: 0.9624 - val_loss: 0.1031 - val_accuracy: 0.9727 - 173s/epoch - 4ms/step diff --git a/doc/listings/denseModel.txt b/doc/listings/denseModel.txt new file mode 100644 index 0000000..006e321 --- /dev/null +++ b/doc/listings/denseModel.txt @@ -0,0 +1,17 @@ +Model: "sequential" +_________________________________________________________________ + Layer (type) Output Shape Param # +================================================================= + dense (Dense) (None, 9, 9, 81) 243 + + dense_1 (Dense) (None, 9, 9, 81) 6642 + + flatten (Flatten) (None, 6561) 0 + + dense_2 (Dense) (None, 82) 538084 + +================================================================= +Total params: 544,969 +Trainable params: 544,969 +Non-trainable params: 0 +_________________________________________________________________ diff --git a/doc/listings/denseTraining.txt b/doc/listings/denseTraining.txt new file mode 100644 index 0000000..0bfcb51 --- /dev/null +++ b/doc/listings/denseTraining.txt @@ -0,0 +1,40 @@ +Epoch 1/20 +148338/148338 - 1151s - loss: 1.1130 - accuracy: 0.6942 - val_loss: 0.6097 - val_accuracy: 0.8249 - 1151s/epoch - 8ms/step +Epoch 2/20 +148338/148338 - 1084s - loss: 0.5366 - accuracy: 0.8572 - val_loss: 0.4744 - val_accuracy: 0.8617 - 1084s/epoch - 7ms/step +Epoch 3/20 +148338/148338 - 1071s - loss: 0.4250 - accuracy: 0.8895 - val_loss: 0.4161 - val_accuracy: 0.8813 - 1071s/epoch - 7ms/step +Epoch 4/20 +148338/148338 - 1118s - loss: 0.3678 - accuracy: 0.9066 - val_loss: 0.3493 - val_accuracy: 0.9024 - 1118s/epoch - 8ms/step +Epoch 5/20 +148338/148338 - 1092s - loss: 0.3320 - accuracy: 0.9170 - val_loss: 0.3103 - val_accuracy: 0.9185 - 1092s/epoch - 7ms/step +Epoch 6/20 +148338/148338 - 1097s - loss: 0.3078 - accuracy: 0.9241 - val_loss: 0.3132 - val_accuracy: 0.9145 - 1097s/epoch - 7ms/step +Epoch 7/20 +148338/148338 - 1074s - loss: 0.2899 - accuracy: 0.9293 - val_loss: 0.2779 - val_accuracy: 0.9257 - 1074s/epoch - 7ms/step +Epoch 8/20 +148338/148338 - 1114s - loss: 0.2762 - accuracy: 0.9330 - val_loss: 0.2709 - val_accuracy: 0.9246 - 1114s/epoch - 8ms/step +Epoch 9/20 +148338/148338 - 1111s - loss: 0.2660 - accuracy: 0.9351 - val_loss: 0.2577 - val_accuracy: 0.9319 - 1111s/epoch - 7ms/step +Epoch 10/20 +148338/148338 - 1104s - loss: 0.2563 - accuracy: 0.9374 - val_loss: 0.2446 - val_accuracy: 0.9388 - 1104s/epoch - 7ms/step +Epoch 11/20 +148338/148338 - 1084s - loss: 0.2489 - accuracy: 0.9394 - val_loss: 0.2441 - val_accuracy: 0.9348 - 1084s/epoch - 7ms/step +Epoch 12/20 +148338/148338 - 1088s - loss: 0.2419 - accuracy: 0.9407 - val_loss: 0.2538 - val_accuracy: 0.9337 - 1088s/epoch - 7ms/step +Epoch 13/20 +148338/148338 - 1090s - loss: 0.2365 - accuracy: 0.9416 - val_loss: 0.2538 - val_accuracy: 0.9312 - 1090s/epoch - 7ms/step +Epoch 14/20 +148338/148338 - 1063s - loss: 0.2314 - accuracy: 0.9430 - val_loss: 0.2484 - val_accuracy: 0.9308 - 1063s/epoch - 7ms/step +Epoch 15/20 +148338/148338 - 1111s - loss: 0.2271 - accuracy: 0.9436 - val_loss: 0.2373 - val_accuracy: 0.9359 - 1111s/epoch - 7ms/step +Epoch 16/20 +148338/148338 - 1124s - loss: 0.2235 - accuracy: 0.9443 - val_loss: 0.2542 - val_accuracy: 0.9257 - 1124s/epoch - 8ms/step +Epoch 17/20 +148338/148338 - 1074s - loss: 0.2202 - accuracy: 0.9451 - val_loss: 0.2368 - val_accuracy: 0.9327 - 1074s/epoch - 7ms/step +Epoch 18/20 +148338/148338 - 1120s - loss: 0.2181 - accuracy: 0.9453 - val_loss: 0.2462 - val_accuracy: 0.9286 - 1120s/epoch - 8ms/step +Epoch 19/20 +148338/148338 - 1121s - loss: 0.2159 - accuracy: 0.9460 - val_loss: 0.2375 - val_accuracy: 0.9316 - 1121s/epoch - 8ms/step +Epoch 20/20 +148338/148338 - 1115s - loss: 0.2154 - accuracy: 0.9458 - val_loss: 0.2273 - val_accuracy: 0.9352 - 1115s/epoch - 8ms/step diff --git a/doc/listings/trainCommand.sh b/doc/listings/trainCommand.sh new file mode 100644 index 0000000..a5f09c4 --- /dev/null +++ b/doc/listings/trainCommand.sh @@ -0,0 +1 @@ +./train.py $(ls ../collections/minigo/matches/*.sgf | shuf | head -n 50) -- cgit v1.2.1