Added Adam env 2 results and fixed folder names

15 files changed, 79 insertions, 0 deletions

diff --git a/training_results/env1/Adagrad_tr001/MNIST b/training_results/env1/Adagrad_lr001/MNIST
index 83ec7df..83ec7df 100644
--- a/training_results/env1/Adagrad_tr001/MNIST
+++ b/training_results/env1/Adagrad_lr001/MNIST
diff --git a/training_results/env1/Adagrad_tr01/MNIST b/training_results/env1/Adagrad_lr01/MNIST
index e55185d..e55185d 100644
--- a/training_results/env1/Adagrad_tr01/MNIST
+++ b/training_results/env1/Adagrad_lr01/MNIST
diff --git a/training_results/env1/Adam_tr001/FashionMNIST b/training_results/env1/Adam_lr001/FashionMNIST
index f6312b0..f6312b0 100644
--- a/training_results/env1/Adam_tr001/FashionMNIST
+++ b/training_results/env1/Adam_lr001/FashionMNIST
diff --git a/training_results/env1/Adam_tr001/MNIST b/training_results/env1/Adam_lr001/MNIST
index e69de29..e69de29 100644
--- a/training_results/env1/Adam_tr001/MNIST
+++ b/training_results/env1/Adam_lr001/MNIST
diff --git a/training_results/env1/Adam_tr01/MNIST b/training_results/env1/Adam_lr01/MNIST
index 6789adc..6789adc 100644
--- a/training_results/env1/Adam_tr01/MNIST
+++ b/training_results/env1/Adam_lr01/MNIST
diff --git a/training_results/env1/NAdam_tr001/MNIST b/training_results/env1/NAdam_lr001/MNIST
index 2e2f4b4..2e2f4b4 100644
--- a/training_results/env1/NAdam_tr001/MNIST
+++ b/training_results/env1/NAdam_lr001/MNIST
diff --git a/training_results/env1/NAdam_tr002/MNIST b/training_results/env1/NAdam_lr002/MNIST
index fd203c8..fd203c8 100644
--- a/training_results/env1/NAdam_tr002/MNIST
+++ b/training_results/env1/NAdam_lr002/MNIST
diff --git a/training_results/env1/ReLU_and_MaxPool_tr001/FashionMNIST b/training_results/env1/ReLU_and_MaxPool_lr001/FashionMNIST
index c4faabb..c4faabb 100644
--- a/training_results/env1/ReLU_and_MaxPool_tr001/FashionMNIST
+++ b/training_results/env1/ReLU_and_MaxPool_lr001/FashionMNIST
diff --git a/training_results/env1/ReLU_and_MaxPool_tr01/FashionMNIST b/training_results/env1/ReLU_and_MaxPool_lr01/FashionMNIST
index da34bb9..da34bb9 100644
--- a/training_results/env1/ReLU_and_MaxPool_tr01/FashionMNIST
+++ b/training_results/env1/ReLU_and_MaxPool_lr01/FashionMNIST
diff --git a/training_results/env1/ReLU_and_MaxPool_tr01/MNIST b/training_results/env1/ReLU_and_MaxPool_lr01/MNIST
index bff64dd..bff64dd 100644
--- a/training_results/env1/ReLU_and_MaxPool_tr01/MNIST
+++ b/training_results/env1/ReLU_and_MaxPool_lr01/MNIST
diff --git a/training_results/env1/ReLU_tr001/FashionMNIST b/training_results/env1/ReLU_lr001/FashionMNIST
index f64566a..f64566a 100644
--- a/training_results/env1/ReLU_tr001/FashionMNIST
+++ b/training_results/env1/ReLU_lr001/FashionMNIST
diff --git a/training_results/env1/ReLU_tr001/MNIST b/training_results/env1/ReLU_lr001/MNIST
index fa0b906..fa0b906 100644
--- a/training_results/env1/ReLU_tr001/MNIST
+++ b/training_results/env1/ReLU_lr001/MNIST
diff --git a/training_results/env1/ReLU_tr01/FashionMNIST b/training_results/env1/ReLU_lr01/FashionMNIST
index da02243..da02243 100644
--- a/training_results/env1/ReLU_tr01/FashionMNIST
+++ b/training_results/env1/ReLU_lr01/FashionMNIST
diff --git a/training_results/env1/ReLU_tr01/MNIST b/training_results/env1/ReLU_lr01/MNIST
index f586eff..f586eff 100644
--- a/training_results/env1/ReLU_tr01/MNIST
+++ b/training_results/env1/ReLU_lr01/MNIST
diff --git a/training_results/env2/Adam/MNIST b/training_results/env2/Adam/MNIST
new file mode 100644
index 0000000..f4b58cd
--- /dev/null
+++ b/training_results/env2/Adam/MNIST
@@ -0,0 +1,79 @@
+Epoch 1 [12800/60000] Loss: 0.136665
+Epoch 1 [25600/60000] Loss: 0.162167
+Epoch 1 [38400/60000] Loss: 0.060944
+Epoch 1 [51200/60000] Loss: 0.117724
+Epoch 1 - Avg Loss: 0.169864, Accuracy: 96.01%
+
+Test Set - Loss: 0.0001, Accuracy: 98.44%
+
+Epoch 2 [12800/60000] Loss: 0.092171
+Epoch 2 [25600/60000] Loss: 0.021338
+Epoch 2 [38400/60000] Loss: 0.094518
+Epoch 2 [51200/60000] Loss: 0.074454
+Epoch 2 - Avg Loss: 0.043798, Accuracy: 99.03%
+
+Test Set - Loss: 0.0000, Accuracy: 98.82%
+
+Epoch 3 [12800/60000] Loss: 0.088897
+Epoch 3 [25600/60000] Loss: 0.015518
+Epoch 3 [38400/60000] Loss: 0.030410
+Epoch 3 [51200/60000] Loss: 0.076697
+Epoch 3 - Avg Loss: 0.030009, Accuracy: 99.36%
+
+Test Set - Loss: 0.0000, Accuracy: 98.93%
+
+Epoch 4 [12800/60000] Loss: 0.008431
+Epoch 4 [25600/60000] Loss: 0.002401
+Epoch 4 [38400/60000] Loss: 0.014520
+Epoch 4 [51200/60000] Loss: 0.025814
+Epoch 4 - Avg Loss: 0.024399, Accuracy: 99.44%
+
+Test Set - Loss: 0.0000, Accuracy: 99.08%
+
+Epoch 5 [12800/60000] Loss: 0.000815
+Epoch 5 [25600/60000] Loss: 0.008576
+Epoch 5 [38400/60000] Loss: 0.003800
+Epoch 5 [51200/60000] Loss: 0.013346
+Epoch 5 - Avg Loss: 0.019088, Accuracy: 99.62%
+
+Test Set - Loss: 0.0000, Accuracy: 98.96%
+
+Epoch 6 [12800/60000] Loss: 0.038003
+Epoch 6 [25600/60000] Loss: 0.010052
+Epoch 6 [38400/60000] Loss: 0.004194
+Epoch 6 [51200/60000] Loss: 0.001696
+Epoch 6 - Avg Loss: 0.014721, Accuracy: 99.73%
+
+Test Set - Loss: 0.0000, Accuracy: 99.13%
+
+Epoch 7 [12800/60000] Loss: 0.007727
+Epoch 7 [25600/60000] Loss: 0.047644
+Epoch 7 [38400/60000] Loss: 0.000464
+Epoch 7 [51200/60000] Loss: 0.000607
+Epoch 7 - Avg Loss: 0.013894, Accuracy: 99.75%
+
+Test Set - Loss: 0.0000, Accuracy: 99.11%
+
+Epoch 8 [12800/60000] Loss: 0.001249
+Epoch 8 [25600/60000] Loss: 0.015864
+Epoch 8 [38400/60000] Loss: 0.012518
+Epoch 8 [51200/60000] Loss: 0.001050
+Epoch 8 - Avg Loss: 0.011323, Accuracy: 99.78%
+
+Test Set - Loss: 0.0000, Accuracy: 99.04%
+
+Epoch 9 [12800/60000] Loss: 0.000285
+Epoch 9 [25600/60000] Loss: 0.002247
+Epoch 9 [38400/60000] Loss: 0.001523
+Epoch 9 [51200/60000] Loss: 0.030761
+Epoch 9 - Avg Loss: 0.010586, Accuracy: 99.82%
+
+Test Set - Loss: 0.0000, Accuracy: 99.11%
+
+Epoch 10 [12800/60000] Loss: 0.000368
+Epoch 10 [25600/60000] Loss: 0.002828
+Epoch 10 [38400/60000] Loss: 0.006644
+Epoch 10 [51200/60000] Loss: 0.000153
+Epoch 10 - Avg Loss: 0.007253, Accuracy: 99.90%
+
+Test Set - Loss: 0.0000, Accuracy: 99.08%