From 501be5542844cae3af5680a69f1c1b0db17d111f Mon Sep 17 00:00:00 2001 From: Jeff Heiges <jeff.heiges@colorado.edu> Date: Wed, 5 Mar 2025 17:05:31 -0700 Subject: Added Adam env 2 results and fixed folder names --- training_results/env1/Adagrad_lr001/MNIST | 29 ++++++++ training_results/env1/Adagrad_lr01/MNIST | 29 ++++++++ training_results/env1/Adagrad_tr001/MNIST | 29 -------- training_results/env1/Adagrad_tr01/MNIST | 29 -------- training_results/env1/Adam_lr001/FashionMNIST | 29 ++++++++ training_results/env1/Adam_lr001/MNIST | 0 training_results/env1/Adam_lr01/MNIST | 29 ++++++++ training_results/env1/Adam_tr001/FashionMNIST | 29 -------- training_results/env1/Adam_tr001/MNIST | 0 training_results/env1/Adam_tr01/MNIST | 29 -------- training_results/env1/NAdam_lr001/MNIST | 29 ++++++++ training_results/env1/NAdam_lr002/MNIST | 29 ++++++++ training_results/env1/NAdam_tr001/MNIST | 29 -------- training_results/env1/NAdam_tr002/MNIST | 29 -------- .../env1/ReLU_and_MaxPool_lr001/FashionMNIST | 29 ++++++++ .../env1/ReLU_and_MaxPool_lr01/FashionMNIST | 29 ++++++++ training_results/env1/ReLU_and_MaxPool_lr01/MNIST | 29 ++++++++ .../env1/ReLU_and_MaxPool_tr001/FashionMNIST | 29 -------- .../env1/ReLU_and_MaxPool_tr01/FashionMNIST | 29 -------- training_results/env1/ReLU_and_MaxPool_tr01/MNIST | 29 -------- training_results/env1/ReLU_lr001/FashionMNIST | 29 ++++++++ training_results/env1/ReLU_lr001/MNIST | 29 ++++++++ training_results/env1/ReLU_lr01/FashionMNIST | 29 ++++++++ training_results/env1/ReLU_lr01/MNIST | 29 ++++++++ training_results/env1/ReLU_tr001/FashionMNIST | 29 -------- training_results/env1/ReLU_tr001/MNIST | 29 -------- training_results/env1/ReLU_tr01/FashionMNIST | 29 -------- training_results/env1/ReLU_tr01/MNIST | 29 -------- training_results/env2/Adam/MNIST | 79 ++++++++++++++++++++++ 29 files changed, 456 insertions(+), 377 deletions(-) create mode 100644 training_results/env1/Adagrad_lr001/MNIST create mode 100644 training_results/env1/Adagrad_lr01/MNIST delete mode 100644 training_results/env1/Adagrad_tr001/MNIST delete mode 100644 training_results/env1/Adagrad_tr01/MNIST create mode 100644 training_results/env1/Adam_lr001/FashionMNIST create mode 100644 training_results/env1/Adam_lr001/MNIST create mode 100644 training_results/env1/Adam_lr01/MNIST delete mode 100644 training_results/env1/Adam_tr001/FashionMNIST delete mode 100644 training_results/env1/Adam_tr001/MNIST delete mode 100644 training_results/env1/Adam_tr01/MNIST create mode 100644 training_results/env1/NAdam_lr001/MNIST create mode 100644 training_results/env1/NAdam_lr002/MNIST delete mode 100644 training_results/env1/NAdam_tr001/MNIST delete mode 100644 training_results/env1/NAdam_tr002/MNIST create mode 100644 training_results/env1/ReLU_and_MaxPool_lr001/FashionMNIST create mode 100644 training_results/env1/ReLU_and_MaxPool_lr01/FashionMNIST create mode 100644 training_results/env1/ReLU_and_MaxPool_lr01/MNIST delete mode 100644 training_results/env1/ReLU_and_MaxPool_tr001/FashionMNIST delete mode 100644 training_results/env1/ReLU_and_MaxPool_tr01/FashionMNIST delete mode 100644 training_results/env1/ReLU_and_MaxPool_tr01/MNIST create mode 100644 training_results/env1/ReLU_lr001/FashionMNIST create mode 100644 training_results/env1/ReLU_lr001/MNIST create mode 100644 training_results/env1/ReLU_lr01/FashionMNIST create mode 100644 training_results/env1/ReLU_lr01/MNIST delete mode 100644 training_results/env1/ReLU_tr001/FashionMNIST delete mode 100644 training_results/env1/ReLU_tr001/MNIST delete mode 100644 training_results/env1/ReLU_tr01/FashionMNIST delete mode 100644 training_results/env1/ReLU_tr01/MNIST create mode 100644 training_results/env2/Adam/MNIST diff --git a/training_results/env1/Adagrad_lr001/MNIST b/training_results/env1/Adagrad_lr001/MNIST new file mode 100644 index 0000000..83ec7df --- /dev/null +++ b/training_results/env1/Adagrad_lr001/MNIST @@ -0,0 +1,29 @@ +MNIST: Epoch 1 - Avg Loss: 0.622060, Accuracy: 83.91% +Test Set - Loss: 0.0003, Accuracy: 90.16% + +MNIST: Epoch 2 - Avg Loss: 0.311773, Accuracy: 90.89% +Test Set - Loss: 0.0003, Accuracy: 92.08% + +MNIST: Epoch 3 - Avg Loss: 0.262124, Accuracy: 92.30% +Test Set - Loss: 0.0002, Accuracy: 93.47% + +MNIST: Epoch 4 - Avg Loss: 0.231953, Accuracy: 93.14% +Test Set - Loss: 0.0002, Accuracy: 93.98% + +MNIST: Epoch 5 - Avg Loss: 0.210415, Accuracy: 93.78% +Test Set - Loss: 0.0002, Accuracy: 94.49% + +MNIST: Epoch 6 - Avg Loss: 0.193878, Accuracy: 94.27% +Test Set - Loss: 0.0002, Accuracy: 94.99% + +MNIST: Epoch 7 - Avg Loss: 0.180249, Accuracy: 94.65% +Test Set - Loss: 0.0002, Accuracy: 95.23% + +MNIST: Epoch 8 - Avg Loss: 0.169277, Accuracy: 94.96% +Test Set - Loss: 0.0001, Accuracy: 95.57% + +MNIST: Epoch 9 - Avg Loss: 0.159998, Accuracy: 95.23% +Test Set - Loss: 0.0001, Accuracy: 95.87% + +MNIST: Epoch 10 - Avg Loss: 0.152065, Accuracy: 95.50% +Test Set - Loss: 0.0001, Accuracy: 96.07% diff --git a/training_results/env1/Adagrad_lr01/MNIST b/training_results/env1/Adagrad_lr01/MNIST new file mode 100644 index 0000000..e55185d --- /dev/null +++ b/training_results/env1/Adagrad_lr01/MNIST @@ -0,0 +1,29 @@ +MNIST: Epoch 1 - Avg Loss: 0.196224, Accuracy: 93.66% +Test Set - Loss: 0.0001, Accuracy: 97.94% + +MNIST: Epoch 2 - Avg Loss: 0.070521, Accuracy: 97.83% +Test Set - Loss: 0.0001, Accuracy: 98.44% + +MNIST: Epoch 3 - Avg Loss: 0.054380, Accuracy: 98.31% +Test Set - Loss: 0.0000, Accuracy: 98.61% + +MNIST: Epoch 4 - Avg Loss: 0.045776, Accuracy: 98.59% +Test Set - Loss: 0.0000, Accuracy: 98.66% + +MNIST: Epoch 5 - Avg Loss: 0.039876, Accuracy: 98.75% +Test Set - Loss: 0.0000, Accuracy: 98.60% + +MNIST: Epoch 6 - Avg Loss: 0.035867, Accuracy: 98.88% +Test Set - Loss: 0.0000, Accuracy: 98.76% + +MNIST: Epoch 7 - Avg Loss: 0.032403, Accuracy: 98.97% +Test Set - Loss: 0.0000, Accuracy: 98.81% + +MNIST: Epoch 8 - Avg Loss: 0.029815, Accuracy: 99.06% +Test Set - Loss: 0.0000, Accuracy: 98.85% + +MNIST: Epoch 9 - Avg Loss: 0.027202, Accuracy: 99.17% +Test Set - Loss: 0.0000, Accuracy: 98.89% + +MNIST: Epoch 10 - Avg Loss: 0.025255, Accuracy: 99.22% +Test Set - Loss: 0.0000, Accuracy: 98.93% diff --git a/training_results/env1/Adagrad_tr001/MNIST b/training_results/env1/Adagrad_tr001/MNIST deleted file mode 100644 index 83ec7df..0000000 --- a/training_results/env1/Adagrad_tr001/MNIST +++ /dev/null @@ -1,29 +0,0 @@ -MNIST: Epoch 1 - Avg Loss: 0.622060, Accuracy: 83.91% -Test Set - Loss: 0.0003, Accuracy: 90.16% - -MNIST: Epoch 2 - Avg Loss: 0.311773, Accuracy: 90.89% -Test Set - Loss: 0.0003, Accuracy: 92.08% - -MNIST: Epoch 3 - Avg Loss: 0.262124, Accuracy: 92.30% -Test Set - Loss: 0.0002, Accuracy: 93.47% - -MNIST: Epoch 4 - Avg Loss: 0.231953, Accuracy: 93.14% -Test Set - Loss: 0.0002, Accuracy: 93.98% - -MNIST: Epoch 5 - Avg Loss: 0.210415, Accuracy: 93.78% -Test Set - Loss: 0.0002, Accuracy: 94.49% - -MNIST: Epoch 6 - Avg Loss: 0.193878, Accuracy: 94.27% -Test Set - Loss: 0.0002, Accuracy: 94.99% - -MNIST: Epoch 7 - Avg Loss: 0.180249, Accuracy: 94.65% -Test Set - Loss: 0.0002, Accuracy: 95.23% - -MNIST: Epoch 8 - Avg Loss: 0.169277, Accuracy: 94.96% -Test Set - Loss: 0.0001, Accuracy: 95.57% - -MNIST: Epoch 9 - Avg Loss: 0.159998, Accuracy: 95.23% -Test Set - Loss: 0.0001, Accuracy: 95.87% - -MNIST: Epoch 10 - Avg Loss: 0.152065, Accuracy: 95.50% -Test Set - Loss: 0.0001, Accuracy: 96.07% diff --git a/training_results/env1/Adagrad_tr01/MNIST b/training_results/env1/Adagrad_tr01/MNIST deleted file mode 100644 index e55185d..0000000 --- a/training_results/env1/Adagrad_tr01/MNIST +++ /dev/null @@ -1,29 +0,0 @@ -MNIST: Epoch 1 - Avg Loss: 0.196224, Accuracy: 93.66% -Test Set - Loss: 0.0001, Accuracy: 97.94% - -MNIST: Epoch 2 - Avg Loss: 0.070521, Accuracy: 97.83% -Test Set - Loss: 0.0001, Accuracy: 98.44% - -MNIST: Epoch 3 - Avg Loss: 0.054380, Accuracy: 98.31% -Test Set - Loss: 0.0000, Accuracy: 98.61% - -MNIST: Epoch 4 - Avg Loss: 0.045776, Accuracy: 98.59% -Test Set - Loss: 0.0000, Accuracy: 98.66% - -MNIST: Epoch 5 - Avg Loss: 0.039876, Accuracy: 98.75% -Test Set - Loss: 0.0000, Accuracy: 98.60% - -MNIST: Epoch 6 - Avg Loss: 0.035867, Accuracy: 98.88% -Test Set - Loss: 0.0000, Accuracy: 98.76% - -MNIST: Epoch 7 - Avg Loss: 0.032403, Accuracy: 98.97% -Test Set - Loss: 0.0000, Accuracy: 98.81% - -MNIST: Epoch 8 - Avg Loss: 0.029815, Accuracy: 99.06% -Test Set - Loss: 0.0000, Accuracy: 98.85% - -MNIST: Epoch 9 - Avg Loss: 0.027202, Accuracy: 99.17% -Test Set - Loss: 0.0000, Accuracy: 98.89% - -MNIST: Epoch 10 - Avg Loss: 0.025255, Accuracy: 99.22% -Test Set - Loss: 0.0000, Accuracy: 98.93% diff --git a/training_results/env1/Adam_lr001/FashionMNIST b/training_results/env1/Adam_lr001/FashionMNIST new file mode 100644 index 0000000..f6312b0 --- /dev/null +++ b/training_results/env1/Adam_lr001/FashionMNIST @@ -0,0 +1,29 @@ +FashionMNIST: Epoch 1 - Avg Loss: 0.566349, Accuracy: 79.38% +Test Set - Loss: 0.0004, Accuracy: 84.45% + +FashionMNIST: Epoch 2 - Avg Loss: 0.366753, Accuracy: 86.74% +Test Set - Loss: 0.0003, Accuracy: 87.65% + +FashionMNIST: Epoch 3 - Avg Loss: 0.317086, Accuracy: 88.42% +Test Set - Loss: 0.0003, Accuracy: 88.62% + +FashionMNIST: Epoch 4 - Avg Loss: 0.291068, Accuracy: 89.23% +Test Set - Loss: 0.0003, Accuracy: 88.46% + +FashionMNIST: Epoch 5 - Avg Loss: 0.265197, Accuracy: 90.19% +Test Set - Loss: 0.0003, Accuracy: 89.16% + +FashionMNIST: Epoch 6 - Avg Loss: 0.249706, Accuracy: 90.68% +Test Set - Loss: 0.0003, Accuracy: 89.36% + +FashionMNIST: Epoch 7 - Avg Loss: 0.235987, Accuracy: 91.27% +Test Set - Loss: 0.0003, Accuracy: 89.66% + +FashionMNIST: Epoch 8 - Avg Loss: 0.219092, Accuracy: 91.76% +Test Set - Loss: 0.0003, Accuracy: 89.26% + +FashionMNIST: Epoch 9 - Avg Loss: 0.207106, Accuracy: 92.19% +Test Set - Loss: 0.0003, Accuracy: 90.35% + +FashionMNIST: Epoch 10 - Avg Loss: 0.195736, Accuracy: 92.54% +Test Set - Loss: 0.0003, Accuracy: 89.90% diff --git a/training_results/env1/Adam_lr001/MNIST b/training_results/env1/Adam_lr001/MNIST new file mode 100644 index 0000000..e69de29 diff --git a/training_results/env1/Adam_lr01/MNIST b/training_results/env1/Adam_lr01/MNIST new file mode 100644 index 0000000..6789adc --- /dev/null +++ b/training_results/env1/Adam_lr01/MNIST @@ -0,0 +1,29 @@ +MNIST: Epoch 1 - Avg Loss: 0.158263, Accuracy: 95.33% +Test Set - Loss: 0.0001, Accuracy: 97.54% + +MNIST: Epoch 2 - Avg Loss: 0.096980, Accuracy: 97.41% +Test Set - Loss: 0.0001, Accuracy: 97.16% + +MNIST: Epoch 3 - Avg Loss: 0.099102, Accuracy: 97.56% +Test Set - Loss: 0.0001, Accuracy: 98.15% + +MNIST: Epoch 4 - Avg Loss: 0.095891, Accuracy: 97.81% +Test Set - Loss: 0.0001, Accuracy: 98.05% + +MNIST: Epoch 5 - Avg Loss: 0.082777, Accuracy: 98.13% +Test Set - Loss: 0.0001, Accuracy: 98.16% + +MNIST: Epoch 6 - Avg Loss: 0.083527, Accuracy: 98.19% +Test Set - Loss: 0.0001, Accuracy: 97.30% + +MNIST: Epoch 7 - Avg Loss: 0.075480, Accuracy: 98.37% +Test Set - Loss: 0.0001, Accuracy: 98.37% + +MNIST: Epoch 8 - Avg Loss: 0.092026, Accuracy: 98.14% +Test Set - Loss: 0.0002, Accuracy: 97.04% + +MNIST: Epoch 9 - Avg Loss: 0.079112, Accuracy: 98.31% +Test Set - Loss: 0.0001, Accuracy: 98.31% + +MNIST: Epoch 10 - Avg Loss: 0.079674, Accuracy: 98.45% +Test Set - Loss: 0.0001, Accuracy: 98.05% diff --git a/training_results/env1/Adam_tr001/FashionMNIST b/training_results/env1/Adam_tr001/FashionMNIST deleted file mode 100644 index f6312b0..0000000 --- a/training_results/env1/Adam_tr001/FashionMNIST +++ /dev/null @@ -1,29 +0,0 @@ -FashionMNIST: Epoch 1 - Avg Loss: 0.566349, Accuracy: 79.38% -Test Set - Loss: 0.0004, Accuracy: 84.45% - -FashionMNIST: Epoch 2 - Avg Loss: 0.366753, Accuracy: 86.74% -Test Set - Loss: 0.0003, Accuracy: 87.65% - -FashionMNIST: Epoch 3 - Avg Loss: 0.317086, Accuracy: 88.42% -Test Set - Loss: 0.0003, Accuracy: 88.62% - -FashionMNIST: Epoch 4 - Avg Loss: 0.291068, Accuracy: 89.23% -Test Set - Loss: 0.0003, Accuracy: 88.46% - -FashionMNIST: Epoch 5 - Avg Loss: 0.265197, Accuracy: 90.19% -Test Set - Loss: 0.0003, Accuracy: 89.16% - -FashionMNIST: Epoch 6 - Avg Loss: 0.249706, Accuracy: 90.68% -Test Set - Loss: 0.0003, Accuracy: 89.36% - -FashionMNIST: Epoch 7 - Avg Loss: 0.235987, Accuracy: 91.27% -Test Set - Loss: 0.0003, Accuracy: 89.66% - -FashionMNIST: Epoch 8 - Avg Loss: 0.219092, Accuracy: 91.76% -Test Set - Loss: 0.0003, Accuracy: 89.26% - -FashionMNIST: Epoch 9 - Avg Loss: 0.207106, Accuracy: 92.19% -Test Set - Loss: 0.0003, Accuracy: 90.35% - -FashionMNIST: Epoch 10 - Avg Loss: 0.195736, Accuracy: 92.54% -Test Set - Loss: 0.0003, Accuracy: 89.90% diff --git a/training_results/env1/Adam_tr001/MNIST b/training_results/env1/Adam_tr001/MNIST deleted file mode 100644 index e69de29..0000000 diff --git a/training_results/env1/Adam_tr01/MNIST b/training_results/env1/Adam_tr01/MNIST deleted file mode 100644 index 6789adc..0000000 --- a/training_results/env1/Adam_tr01/MNIST +++ /dev/null @@ -1,29 +0,0 @@ -MNIST: Epoch 1 - Avg Loss: 0.158263, Accuracy: 95.33% -Test Set - Loss: 0.0001, Accuracy: 97.54% - -MNIST: Epoch 2 - Avg Loss: 0.096980, Accuracy: 97.41% -Test Set - Loss: 0.0001, Accuracy: 97.16% - -MNIST: Epoch 3 - Avg Loss: 0.099102, Accuracy: 97.56% -Test Set - Loss: 0.0001, Accuracy: 98.15% - -MNIST: Epoch 4 - Avg Loss: 0.095891, Accuracy: 97.81% -Test Set - Loss: 0.0001, Accuracy: 98.05% - -MNIST: Epoch 5 - Avg Loss: 0.082777, Accuracy: 98.13% -Test Set - Loss: 0.0001, Accuracy: 98.16% - -MNIST: Epoch 6 - Avg Loss: 0.083527, Accuracy: 98.19% -Test Set - Loss: 0.0001, Accuracy: 97.30% - -MNIST: Epoch 7 - Avg Loss: 0.075480, Accuracy: 98.37% -Test Set - Loss: 0.0001, Accuracy: 98.37% - -MNIST: Epoch 8 - Avg Loss: 0.092026, Accuracy: 98.14% -Test Set - Loss: 0.0002, Accuracy: 97.04% - -MNIST: Epoch 9 - Avg Loss: 0.079112, Accuracy: 98.31% -Test Set - Loss: 0.0001, Accuracy: 98.31% - -MNIST: Epoch 10 - Avg Loss: 0.079674, Accuracy: 98.45% -Test Set - Loss: 0.0001, Accuracy: 98.05% diff --git a/training_results/env1/NAdam_lr001/MNIST b/training_results/env1/NAdam_lr001/MNIST new file mode 100644 index 0000000..2e2f4b4 --- /dev/null +++ b/training_results/env1/NAdam_lr001/MNIST @@ -0,0 +1,29 @@ +MNIST: Epoch 1 - Avg Loss: 0.218898, Accuracy: 93.39% +Test Set - Loss: 0.0001, Accuracy: 97.38% + +MNIST: Epoch 2 - Avg Loss: 0.062066, Accuracy: 98.09% +Test Set - Loss: 0.0001, Accuracy: 97.50% + +MNIST: Epoch 3 - Avg Loss: 0.043854, Accuracy: 98.60% +Test Set - Loss: 0.0000, Accuracy: 98.73% + +MNIST: Epoch 4 - Avg Loss: 0.034842, Accuracy: 98.91% +Test Set - Loss: 0.0000, Accuracy: 98.88% + +MNIST: Epoch 5 - Avg Loss: 0.028108, Accuracy: 99.09% +Test Set - Loss: 0.0000, Accuracy: 98.96% + +MNIST: Epoch 6 - Avg Loss: 0.024074, Accuracy: 99.23% +Test Set - Loss: 0.0000, Accuracy: 98.89% + +MNIST: Epoch 7 - Avg Loss: 0.020622, Accuracy: 99.30% +Test Set - Loss: 0.0000, Accuracy: 98.91% + +MNIST: Epoch 8 - Avg Loss: 0.017064, Accuracy: 99.45% +Test Set - Loss: 0.0000, Accuracy: 98.89% + +MNIST: Epoch 9 - Avg Loss: 0.015592, Accuracy: 99.47% +Test Set - Loss: 0.0000, Accuracy: 98.86% + +MNIST: Epoch 10 - Avg Loss: 0.014128, Accuracy: 99.53% +Test Set - Loss: 0.0000, Accuracy: 99.08% diff --git a/training_results/env1/NAdam_lr002/MNIST b/training_results/env1/NAdam_lr002/MNIST new file mode 100644 index 0000000..fd203c8 --- /dev/null +++ b/training_results/env1/NAdam_lr002/MNIST @@ -0,0 +1,29 @@ +MNIST: Epoch 1 - Avg Loss: 0.160434, Accuracy: 95.00% +Test Set - Loss: 0.0001, Accuracy: 98.29% + +MNIST: Epoch 2 - Avg Loss: 0.049701, Accuracy: 98.47% +Test Set - Loss: 0.0000, Accuracy: 98.66% + +MNIST: Epoch 3 - Avg Loss: 0.037278, Accuracy: 98.83% +Test Set - Loss: 0.0000, Accuracy: 98.51% + +MNIST: Epoch 4 - Avg Loss: 0.031198, Accuracy: 99.04% +Test Set - Loss: 0.0000, Accuracy: 98.76% + +MNIST: Epoch 5 - Avg Loss: 0.026165, Accuracy: 99.18% +Test Set - Loss: 0.0000, Accuracy: 98.88% + +MNIST: Epoch 6 - Avg Loss: 0.024116, Accuracy: 99.25% +Test Set - Loss: 0.0000, Accuracy: 98.91% + +MNIST: Epoch 7 - Avg Loss: 0.020606, Accuracy: 99.33% +Test Set - Loss: 0.0000, Accuracy: 98.86% + +MNIST: Epoch 8 - Avg Loss: 0.018274, Accuracy: 99.44% +Test Set - Loss: 0.0000, Accuracy: 98.91% + +MNIST: Epoch 9 - Avg Loss: 0.018810, Accuracy: 99.46% +Test Set - Loss: 0.0000, Accuracy: 99.01% + +MNIST: Epoch 10 - Avg Loss: 0.015997, Accuracy: 99.50% +Test Set - Loss: 0.0000, Accuracy: 98.87% diff --git a/training_results/env1/NAdam_tr001/MNIST b/training_results/env1/NAdam_tr001/MNIST deleted file mode 100644 index 2e2f4b4..0000000 --- a/training_results/env1/NAdam_tr001/MNIST +++ /dev/null @@ -1,29 +0,0 @@ -MNIST: Epoch 1 - Avg Loss: 0.218898, Accuracy: 93.39% -Test Set - Loss: 0.0001, Accuracy: 97.38% - -MNIST: Epoch 2 - Avg Loss: 0.062066, Accuracy: 98.09% -Test Set - Loss: 0.0001, Accuracy: 97.50% - -MNIST: Epoch 3 - Avg Loss: 0.043854, Accuracy: 98.60% -Test Set - Loss: 0.0000, Accuracy: 98.73% - -MNIST: Epoch 4 - Avg Loss: 0.034842, Accuracy: 98.91% -Test Set - Loss: 0.0000, Accuracy: 98.88% - -MNIST: Epoch 5 - Avg Loss: 0.028108, Accuracy: 99.09% -Test Set - Loss: 0.0000, Accuracy: 98.96% - -MNIST: Epoch 6 - Avg Loss: 0.024074, Accuracy: 99.23% -Test Set - Loss: 0.0000, Accuracy: 98.89% - -MNIST: Epoch 7 - Avg Loss: 0.020622, Accuracy: 99.30% -Test Set - Loss: 0.0000, Accuracy: 98.91% - -MNIST: Epoch 8 - Avg Loss: 0.017064, Accuracy: 99.45% -Test Set - Loss: 0.0000, Accuracy: 98.89% - -MNIST: Epoch 9 - Avg Loss: 0.015592, Accuracy: 99.47% -Test Set - Loss: 0.0000, Accuracy: 98.86% - -MNIST: Epoch 10 - Avg Loss: 0.014128, Accuracy: 99.53% -Test Set - Loss: 0.0000, Accuracy: 99.08% diff --git a/training_results/env1/NAdam_tr002/MNIST b/training_results/env1/NAdam_tr002/MNIST deleted file mode 100644 index fd203c8..0000000 --- a/training_results/env1/NAdam_tr002/MNIST +++ /dev/null @@ -1,29 +0,0 @@ -MNIST: Epoch 1 - Avg Loss: 0.160434, Accuracy: 95.00% -Test Set - Loss: 0.0001, Accuracy: 98.29% - -MNIST: Epoch 2 - Avg Loss: 0.049701, Accuracy: 98.47% -Test Set - Loss: 0.0000, Accuracy: 98.66% - -MNIST: Epoch 3 - Avg Loss: 0.037278, Accuracy: 98.83% -Test Set - Loss: 0.0000, Accuracy: 98.51% - -MNIST: Epoch 4 - Avg Loss: 0.031198, Accuracy: 99.04% -Test Set - Loss: 0.0000, Accuracy: 98.76% - -MNIST: Epoch 5 - Avg Loss: 0.026165, Accuracy: 99.18% -Test Set - Loss: 0.0000, Accuracy: 98.88% - -MNIST: Epoch 6 - Avg Loss: 0.024116, Accuracy: 99.25% -Test Set - Loss: 0.0000, Accuracy: 98.91% - -MNIST: Epoch 7 - Avg Loss: 0.020606, Accuracy: 99.33% -Test Set - Loss: 0.0000, Accuracy: 98.86% - -MNIST: Epoch 8 - Avg Loss: 0.018274, Accuracy: 99.44% -Test Set - Loss: 0.0000, Accuracy: 98.91% - -MNIST: Epoch 9 - Avg Loss: 0.018810, Accuracy: 99.46% -Test Set - Loss: 0.0000, Accuracy: 99.01% - -MNIST: Epoch 10 - Avg Loss: 0.015997, Accuracy: 99.50% -Test Set - Loss: 0.0000, Accuracy: 98.87% diff --git a/training_results/env1/ReLU_and_MaxPool_lr001/FashionMNIST b/training_results/env1/ReLU_and_MaxPool_lr001/FashionMNIST new file mode 100644 index 0000000..c4faabb --- /dev/null +++ b/training_results/env1/ReLU_and_MaxPool_lr001/FashionMNIST @@ -0,0 +1,29 @@ +FashionMNIST: Epoch 1 - Avg Loss: 1.269764, Accuracy: 53.37% +Test Set - Loss: 0.0008, Accuracy: 69.32% + +FashionMNIST: Epoch 2 - Avg Loss: 0.650261, Accuracy: 75.55% +Test Set - Loss: 0.0006, Accuracy: 76.00% + +FashionMNIST: Epoch 3 - Avg Loss: 0.538035, Accuracy: 80.05% +Test Set - Loss: 0.0005, Accuracy: 80.03% + +FashionMNIST: Epoch 4 - Avg Loss: 0.475396, Accuracy: 82.75% +Test Set - Loss: 0.0005, Accuracy: 83.63% + +FashionMNIST: Epoch 5 - Avg Loss: 0.423538, Accuracy: 84.75% +Test Set - Loss: 0.0004, Accuracy: 84.55% + +FashionMNIST: Epoch 6 - Avg Loss: 0.392266, Accuracy: 85.91% +Test Set - Loss: 0.0004, Accuracy: 85.49% + +FashionMNIST: Epoch 7 - Avg Loss: 0.373056, Accuracy: 86.62% +Test Set - Loss: 0.0004, Accuracy: 86.19% + +FashionMNIST: Epoch 8 - Avg Loss: 0.357183, Accuracy: 87.00% +Test Set - Loss: 0.0004, Accuracy: 86.81% + +FashionMNIST: Epoch 9 - Avg Loss: 0.341907, Accuracy: 87.57% +Test Set - Loss: 0.0004, Accuracy: 86.50% + +FashionMNIST: Epoch 10 - Avg Loss: 0.329416, Accuracy: 88.11% +Test Set - Loss: 0.0004, Accuracy: 87.21% diff --git a/training_results/env1/ReLU_and_MaxPool_lr01/FashionMNIST b/training_results/env1/ReLU_and_MaxPool_lr01/FashionMNIST new file mode 100644 index 0000000..da34bb9 --- /dev/null +++ b/training_results/env1/ReLU_and_MaxPool_lr01/FashionMNIST @@ -0,0 +1,29 @@ +FashionMNIST: Epoch 1 - Avg Loss: 0.667863, Accuracy: 75.25% +Test Set - Loss: 0.0004, Accuracy: 84.99% + +FashionMNIST: Epoch 2 - Avg Loss: 0.371554, Accuracy: 86.36% +Test Set - Loss: 0.0004, Accuracy: 86.15% + +FashionMNIST: Epoch 3 - Avg Loss: 0.312804, Accuracy: 88.56% +Test Set - Loss: 0.0003, Accuracy: 87.54% + +FashionMNIST: Epoch 4 - Avg Loss: 0.282618, Accuracy: 89.51% +Test Set - Loss: 0.0003, Accuracy: 88.09% + +FashionMNIST: Epoch 5 - Avg Loss: 0.261221, Accuracy: 90.27% +Test Set - Loss: 0.0003, Accuracy: 89.01% + +FashionMNIST: Epoch 6 - Avg Loss: 0.244058, Accuracy: 90.91% +Test Set - Loss: 0.0003, Accuracy: 89.38% + +FashionMNIST: Epoch 7 - Avg Loss: 0.232460, Accuracy: 91.37% +Test Set - Loss: 0.0003, Accuracy: 89.06% + +FashionMNIST: Epoch 8 - Avg Loss: 0.220620, Accuracy: 91.66% +Test Set - Loss: 0.0003, Accuracy: 89.24% + +FashionMNIST: Epoch 9 - Avg Loss: 0.212714, Accuracy: 92.06% +Test Set - Loss: 0.0003, Accuracy: 89.30% + +FashionMNIST: Epoch 10 - Avg Loss: 0.203891, Accuracy: 92.35% +Test Set - Loss: 0.0003, Accuracy: 90.45% diff --git a/training_results/env1/ReLU_and_MaxPool_lr01/MNIST b/training_results/env1/ReLU_and_MaxPool_lr01/MNIST new file mode 100644 index 0000000..bff64dd --- /dev/null +++ b/training_results/env1/ReLU_and_MaxPool_lr01/MNIST @@ -0,0 +1,29 @@ +MNIST: Epoch 1 - Avg Loss: 0.312942, Accuracy: 90.23% +Test Set - Loss: 0.0001, Accuracy: 98.16% + +MNIST: Epoch 2 - Avg Loss: 0.063010, Accuracy: 98.01% +Test Set - Loss: 0.0001, Accuracy: 97.98% + +MNIST: Epoch 3 - Avg Loss: 0.043627, Accuracy: 98.63% +Test Set - Loss: 0.0000, Accuracy: 98.62% + +MNIST: Epoch 4 - Avg Loss: 0.035296, Accuracy: 98.90% +Test Set - Loss: 0.0000, Accuracy: 98.77% + +MNIST: Epoch 5 - Avg Loss: 0.029064, Accuracy: 99.07% +Test Set - Loss: 0.0000, Accuracy: 98.91% + +MNIST: Epoch 6 - Avg Loss: 0.023820, Accuracy: 99.22% +Test Set - Loss: 0.0000, Accuracy: 98.68% + +MNIST: Epoch 7 - Avg Loss: 0.018958, Accuracy: 99.40% +Test Set - Loss: 0.0000, Accuracy: 98.88% + +MNIST: Epoch 8 - Avg Loss: 0.016465, Accuracy: 99.45% +Test Set - Loss: 0.0000, Accuracy: 99.03% + +MNIST: Epoch 9 - Avg Loss: 0.015039, Accuracy: 99.49% +Test Set - Loss: 0.0000, Accuracy: 99.07% + +MNIST: Epoch 10 - Avg Loss: 0.012170, Accuracy: 99.61% +Test Set - Loss: 0.0000, Accuracy: 99.02% diff --git a/training_results/env1/ReLU_and_MaxPool_tr001/FashionMNIST b/training_results/env1/ReLU_and_MaxPool_tr001/FashionMNIST deleted file mode 100644 index c4faabb..0000000 --- a/training_results/env1/ReLU_and_MaxPool_tr001/FashionMNIST +++ /dev/null @@ -1,29 +0,0 @@ -FashionMNIST: Epoch 1 - Avg Loss: 1.269764, Accuracy: 53.37% -Test Set - Loss: 0.0008, Accuracy: 69.32% - -FashionMNIST: Epoch 2 - Avg Loss: 0.650261, Accuracy: 75.55% -Test Set - Loss: 0.0006, Accuracy: 76.00% - -FashionMNIST: Epoch 3 - Avg Loss: 0.538035, Accuracy: 80.05% -Test Set - Loss: 0.0005, Accuracy: 80.03% - -FashionMNIST: Epoch 4 - Avg Loss: 0.475396, Accuracy: 82.75% -Test Set - Loss: 0.0005, Accuracy: 83.63% - -FashionMNIST: Epoch 5 - Avg Loss: 0.423538, Accuracy: 84.75% -Test Set - Loss: 0.0004, Accuracy: 84.55% - -FashionMNIST: Epoch 6 - Avg Loss: 0.392266, Accuracy: 85.91% -Test Set - Loss: 0.0004, Accuracy: 85.49% - -FashionMNIST: Epoch 7 - Avg Loss: 0.373056, Accuracy: 86.62% -Test Set - Loss: 0.0004, Accuracy: 86.19% - -FashionMNIST: Epoch 8 - Avg Loss: 0.357183, Accuracy: 87.00% -Test Set - Loss: 0.0004, Accuracy: 86.81% - -FashionMNIST: Epoch 9 - Avg Loss: 0.341907, Accuracy: 87.57% -Test Set - Loss: 0.0004, Accuracy: 86.50% - -FashionMNIST: Epoch 10 - Avg Loss: 0.329416, Accuracy: 88.11% -Test Set - Loss: 0.0004, Accuracy: 87.21% diff --git a/training_results/env1/ReLU_and_MaxPool_tr01/FashionMNIST b/training_results/env1/ReLU_and_MaxPool_tr01/FashionMNIST deleted file mode 100644 index da34bb9..0000000 --- a/training_results/env1/ReLU_and_MaxPool_tr01/FashionMNIST +++ /dev/null @@ -1,29 +0,0 @@ -FashionMNIST: Epoch 1 - Avg Loss: 0.667863, Accuracy: 75.25% -Test Set - Loss: 0.0004, Accuracy: 84.99% - -FashionMNIST: Epoch 2 - Avg Loss: 0.371554, Accuracy: 86.36% -Test Set - Loss: 0.0004, Accuracy: 86.15% - -FashionMNIST: Epoch 3 - Avg Loss: 0.312804, Accuracy: 88.56% -Test Set - Loss: 0.0003, Accuracy: 87.54% - -FashionMNIST: Epoch 4 - Avg Loss: 0.282618, Accuracy: 89.51% -Test Set - Loss: 0.0003, Accuracy: 88.09% - -FashionMNIST: Epoch 5 - Avg Loss: 0.261221, Accuracy: 90.27% -Test Set - Loss: 0.0003, Accuracy: 89.01% - -FashionMNIST: Epoch 6 - Avg Loss: 0.244058, Accuracy: 90.91% -Test Set - Loss: 0.0003, Accuracy: 89.38% - -FashionMNIST: Epoch 7 - Avg Loss: 0.232460, Accuracy: 91.37% -Test Set - Loss: 0.0003, Accuracy: 89.06% - -FashionMNIST: Epoch 8 - Avg Loss: 0.220620, Accuracy: 91.66% -Test Set - Loss: 0.0003, Accuracy: 89.24% - -FashionMNIST: Epoch 9 - Avg Loss: 0.212714, Accuracy: 92.06% -Test Set - Loss: 0.0003, Accuracy: 89.30% - -FashionMNIST: Epoch 10 - Avg Loss: 0.203891, Accuracy: 92.35% -Test Set - Loss: 0.0003, Accuracy: 90.45% diff --git a/training_results/env1/ReLU_and_MaxPool_tr01/MNIST b/training_results/env1/ReLU_and_MaxPool_tr01/MNIST deleted file mode 100644 index bff64dd..0000000 --- a/training_results/env1/ReLU_and_MaxPool_tr01/MNIST +++ /dev/null @@ -1,29 +0,0 @@ -MNIST: Epoch 1 - Avg Loss: 0.312942, Accuracy: 90.23% -Test Set - Loss: 0.0001, Accuracy: 98.16% - -MNIST: Epoch 2 - Avg Loss: 0.063010, Accuracy: 98.01% -Test Set - Loss: 0.0001, Accuracy: 97.98% - -MNIST: Epoch 3 - Avg Loss: 0.043627, Accuracy: 98.63% -Test Set - Loss: 0.0000, Accuracy: 98.62% - -MNIST: Epoch 4 - Avg Loss: 0.035296, Accuracy: 98.90% -Test Set - Loss: 0.0000, Accuracy: 98.77% - -MNIST: Epoch 5 - Avg Loss: 0.029064, Accuracy: 99.07% -Test Set - Loss: 0.0000, Accuracy: 98.91% - -MNIST: Epoch 6 - Avg Loss: 0.023820, Accuracy: 99.22% -Test Set - Loss: 0.0000, Accuracy: 98.68% - -MNIST: Epoch 7 - Avg Loss: 0.018958, Accuracy: 99.40% -Test Set - Loss: 0.0000, Accuracy: 98.88% - -MNIST: Epoch 8 - Avg Loss: 0.016465, Accuracy: 99.45% -Test Set - Loss: 0.0000, Accuracy: 99.03% - -MNIST: Epoch 9 - Avg Loss: 0.015039, Accuracy: 99.49% -Test Set - Loss: 0.0000, Accuracy: 99.07% - -MNIST: Epoch 10 - Avg Loss: 0.012170, Accuracy: 99.61% -Test Set - Loss: 0.0000, Accuracy: 99.02% diff --git a/training_results/env1/ReLU_lr001/FashionMNIST b/training_results/env1/ReLU_lr001/FashionMNIST new file mode 100644 index 0000000..f64566a --- /dev/null +++ b/training_results/env1/ReLU_lr001/FashionMNIST @@ -0,0 +1,29 @@ +FashionMNIST: Epoch 1 - Avg Loss: 2.286776, Accuracy: 11.10% +Test Set - Loss: 0.0023, Accuracy: 20.23% + +FashionMNIST: Epoch 2 - Avg Loss: 2.093157, Accuracy: 28.33% +Test Set - Loss: 0.0017, Accuracy: 43.26% + +FashionMNIST: Epoch 3 - Avg Loss: 1.219165, Accuracy: 59.18% +Test Set - Loss: 0.0010, Accuracy: 64.76% + +FashionMNIST: Epoch 4 - Avg Loss: 0.898229, Accuracy: 66.46% +Test Set - Loss: 0.0009, Accuracy: 67.72% + +FashionMNIST: Epoch 5 - Avg Loss: 0.829833, Accuracy: 69.22% +Test Set - Loss: 0.0008, Accuracy: 68.84% + +FashionMNIST: Epoch 6 - Avg Loss: 0.793659, Accuracy: 70.45% +Test Set - Loss: 0.0008, Accuracy: 71.13% + +FashionMNIST: Epoch 7 - Avg Loss: 0.767977, Accuracy: 71.28% +Test Set - Loss: 0.0008, Accuracy: 66.79% + +FashionMNIST: Epoch 8 - Avg Loss: 0.745336, Accuracy: 72.42% +Test Set - Loss: 0.0008, Accuracy: 72.50% + +FashionMNIST: Epoch 9 - Avg Loss: 0.726640, Accuracy: 73.26% +Test Set - Loss: 0.0008, Accuracy: 72.69% + +FashionMNIST: Epoch 10 - Avg Loss: 0.710800, Accuracy: 73.79% +Test Set - Loss: 0.0007, Accuracy: 72.53% diff --git a/training_results/env1/ReLU_lr001/MNIST b/training_results/env1/ReLU_lr001/MNIST new file mode 100644 index 0000000..fa0b906 --- /dev/null +++ b/training_results/env1/ReLU_lr001/MNIST @@ -0,0 +1,29 @@ +MNIST: Epoch 1 - Avg Loss: 2.301629, Accuracy: 12.35% +Test Set - Loss: 0.0023, Accuracy: 13.35% + +MNIST: Epoch 2 - Avg Loss: 2.297156, Accuracy: 14.30% +Test Set - Loss: 0.0023, Accuracy: 14.97% + +MNIST: Epoch 3 - Avg Loss: 2.290805, Accuracy: 19.35% +Test Set - Loss: 0.0023, Accuracy: 26.36% + +MNIST: Epoch 4 - Avg Loss: 2.278976, Accuracy: 32.53% +Test Set - Loss: 0.0023, Accuracy: 36.21% + +MNIST: Epoch 5 - Avg Loss: 2.247882, Accuracy: 37.81% +Test Set - Loss: 0.0022, Accuracy: 38.21% + +MNIST: Epoch 6 - Avg Loss: 2.111991, Accuracy: 45.10% +Test Set - Loss: 0.0019, Accuracy: 55.52% + +MNIST: Epoch 7 - Avg Loss: 1.385476, Accuracy: 68.85% +Test Set - Loss: 0.0009, Accuracy: 78.59% + +MNIST: Epoch 8 - Avg Loss: 0.709682, Accuracy: 80.62% +Test Set - Loss: 0.0006, Accuracy: 83.57% + +MNIST: Epoch 9 - Avg Loss: 0.551874, Accuracy: 84.08% +Test Set - Loss: 0.0005, Accuracy: 85.80% + +MNIST: Epoch 10 - Avg Loss: 0.481764, Accuracy: 85.94% +Test Set - Loss: 0.0004, Accuracy: 87.28% diff --git a/training_results/env1/ReLU_lr01/FashionMNIST b/training_results/env1/ReLU_lr01/FashionMNIST new file mode 100644 index 0000000..da02243 --- /dev/null +++ b/training_results/env1/ReLU_lr01/FashionMNIST @@ -0,0 +1,29 @@ +FashionMNIST: Epoch 1 - Avg Loss: 0.743093, Accuracy: 72.53% +Test Set - Loss: 0.0005, Accuracy: 81.53% + +FashionMNIST: Epoch 2 - Avg Loss: 0.411287, Accuracy: 84.85% +Test Set - Loss: 0.0004, Accuracy: 85.97% + +FashionMNIST: Epoch 3 - Avg Loss: 0.353779, Accuracy: 86.93% +Test Set - Loss: 0.0004, Accuracy: 86.91% + +FashionMNIST: Epoch 4 - Avg Loss: 0.315969, Accuracy: 88.33% +Test Set - Loss: 0.0004, Accuracy: 87.19% + +FashionMNIST: Epoch 5 - Avg Loss: 0.293813, Accuracy: 89.04% +Test Set - Loss: 0.0003, Accuracy: 87.88% + +FashionMNIST: Epoch 6 - Avg Loss: 0.275946, Accuracy: 89.68% +Test Set - Loss: 0.0003, Accuracy: 88.43% + +FashionMNIST: Epoch 7 - Avg Loss: 0.262246, Accuracy: 90.34% +Test Set - Loss: 0.0003, Accuracy: 89.06% + +FashionMNIST: Epoch 8 - Avg Loss: 0.246963, Accuracy: 90.76% +Test Set - Loss: 0.0003, Accuracy: 89.54% + +FashionMNIST: Epoch 9 - Avg Loss: 0.238650, Accuracy: 91.13% +Test Set - Loss: 0.0003, Accuracy: 89.51% + +FashionMNIST: Epoch 10 - Avg Loss: 0.229345, Accuracy: 91.46% +Test Set - Loss: 0.0003, Accuracy: 90.22% diff --git a/training_results/env1/ReLU_lr01/MNIST b/training_results/env1/ReLU_lr01/MNIST new file mode 100644 index 0000000..f586eff --- /dev/null +++ b/training_results/env1/ReLU_lr01/MNIST @@ -0,0 +1,29 @@ +MNIST: Epoch 1 - Avg Loss: 0.426265, Accuracy: 87.01% +Test Set - Loss: 0.0001, Accuracy: 96.91% + +MNIST: Epoch 2 - Avg Loss: 0.082446, Accuracy: 97.52% +Test Set - Loss: 0.0001, Accuracy: 98.33% + +MNIST: Epoch 3 - Avg Loss: 0.054633, Accuracy: 98.32% +Test Set - Loss: 0.0000, Accuracy: 98.62% + +MNIST: Epoch 4 - Avg Loss: 0.041592, Accuracy: 98.72% +Test Set - Loss: 0.0000, Accuracy: 98.73% + +MNIST: Epoch 5 - Avg Loss: 0.035133, Accuracy: 98.88% +Test Set - Loss: 0.0000, Accuracy: 98.81% + +MNIST: Epoch 6 - Avg Loss: 0.028988, Accuracy: 99.05% +Test Set - Loss: 0.0000, Accuracy: 98.76% + +MNIST: Epoch 7 - Avg Loss: 0.025236, Accuracy: 99.16% +Test Set - Loss: 0.0000, Accuracy: 98.58% + +MNIST: Epoch 8 - Avg Loss: 0.022040, Accuracy: 99.31% +Test Set - Loss: 0.0000, Accuracy: 98.85% + +MNIST: Epoch 9 - Avg Loss: 0.019295, Accuracy: 99.39% +Test Set - Loss: 0.0000, Accuracy: 98.94% + +MNIST: Epoch 10 - Avg Loss: 0.015332, Accuracy: 99.50% +Test Set - Loss: 0.0000, Accuracy: 98.91% diff --git a/training_results/env1/ReLU_tr001/FashionMNIST b/training_results/env1/ReLU_tr001/FashionMNIST deleted file mode 100644 index f64566a..0000000 --- a/training_results/env1/ReLU_tr001/FashionMNIST +++ /dev/null @@ -1,29 +0,0 @@ -FashionMNIST: Epoch 1 - Avg Loss: 2.286776, Accuracy: 11.10% -Test Set - Loss: 0.0023, Accuracy: 20.23% - -FashionMNIST: Epoch 2 - Avg Loss: 2.093157, Accuracy: 28.33% -Test Set - Loss: 0.0017, Accuracy: 43.26% - -FashionMNIST: Epoch 3 - Avg Loss: 1.219165, Accuracy: 59.18% -Test Set - Loss: 0.0010, Accuracy: 64.76% - -FashionMNIST: Epoch 4 - Avg Loss: 0.898229, Accuracy: 66.46% -Test Set - Loss: 0.0009, Accuracy: 67.72% - -FashionMNIST: Epoch 5 - Avg Loss: 0.829833, Accuracy: 69.22% -Test Set - Loss: 0.0008, Accuracy: 68.84% - -FashionMNIST: Epoch 6 - Avg Loss: 0.793659, Accuracy: 70.45% -Test Set - Loss: 0.0008, Accuracy: 71.13% - -FashionMNIST: Epoch 7 - Avg Loss: 0.767977, Accuracy: 71.28% -Test Set - Loss: 0.0008, Accuracy: 66.79% - -FashionMNIST: Epoch 8 - Avg Loss: 0.745336, Accuracy: 72.42% -Test Set - Loss: 0.0008, Accuracy: 72.50% - -FashionMNIST: Epoch 9 - Avg Loss: 0.726640, Accuracy: 73.26% -Test Set - Loss: 0.0008, Accuracy: 72.69% - -FashionMNIST: Epoch 10 - Avg Loss: 0.710800, Accuracy: 73.79% -Test Set - Loss: 0.0007, Accuracy: 72.53% diff --git a/training_results/env1/ReLU_tr001/MNIST b/training_results/env1/ReLU_tr001/MNIST deleted file mode 100644 index fa0b906..0000000 --- a/training_results/env1/ReLU_tr001/MNIST +++ /dev/null @@ -1,29 +0,0 @@ -MNIST: Epoch 1 - Avg Loss: 2.301629, Accuracy: 12.35% -Test Set - Loss: 0.0023, Accuracy: 13.35% - -MNIST: Epoch 2 - Avg Loss: 2.297156, Accuracy: 14.30% -Test Set - Loss: 0.0023, Accuracy: 14.97% - -MNIST: Epoch 3 - Avg Loss: 2.290805, Accuracy: 19.35% -Test Set - Loss: 0.0023, Accuracy: 26.36% - -MNIST: Epoch 4 - Avg Loss: 2.278976, Accuracy: 32.53% -Test Set - Loss: 0.0023, Accuracy: 36.21% - -MNIST: Epoch 5 - Avg Loss: 2.247882, Accuracy: 37.81% -Test Set - Loss: 0.0022, Accuracy: 38.21% - -MNIST: Epoch 6 - Avg Loss: 2.111991, Accuracy: 45.10% -Test Set - Loss: 0.0019, Accuracy: 55.52% - -MNIST: Epoch 7 - Avg Loss: 1.385476, Accuracy: 68.85% -Test Set - Loss: 0.0009, Accuracy: 78.59% - -MNIST: Epoch 8 - Avg Loss: 0.709682, Accuracy: 80.62% -Test Set - Loss: 0.0006, Accuracy: 83.57% - -MNIST: Epoch 9 - Avg Loss: 0.551874, Accuracy: 84.08% -Test Set - Loss: 0.0005, Accuracy: 85.80% - -MNIST: Epoch 10 - Avg Loss: 0.481764, Accuracy: 85.94% -Test Set - Loss: 0.0004, Accuracy: 87.28% diff --git a/training_results/env1/ReLU_tr01/FashionMNIST b/training_results/env1/ReLU_tr01/FashionMNIST deleted file mode 100644 index da02243..0000000 --- a/training_results/env1/ReLU_tr01/FashionMNIST +++ /dev/null @@ -1,29 +0,0 @@ -FashionMNIST: Epoch 1 - Avg Loss: 0.743093, Accuracy: 72.53% -Test Set - Loss: 0.0005, Accuracy: 81.53% - -FashionMNIST: Epoch 2 - Avg Loss: 0.411287, Accuracy: 84.85% -Test Set - Loss: 0.0004, Accuracy: 85.97% - -FashionMNIST: Epoch 3 - Avg Loss: 0.353779, Accuracy: 86.93% -Test Set - Loss: 0.0004, Accuracy: 86.91% - -FashionMNIST: Epoch 4 - Avg Loss: 0.315969, Accuracy: 88.33% -Test Set - Loss: 0.0004, Accuracy: 87.19% - -FashionMNIST: Epoch 5 - Avg Loss: 0.293813, Accuracy: 89.04% -Test Set - Loss: 0.0003, Accuracy: 87.88% - -FashionMNIST: Epoch 6 - Avg Loss: 0.275946, Accuracy: 89.68% -Test Set - Loss: 0.0003, Accuracy: 88.43% - -FashionMNIST: Epoch 7 - Avg Loss: 0.262246, Accuracy: 90.34% -Test Set - Loss: 0.0003, Accuracy: 89.06% - -FashionMNIST: Epoch 8 - Avg Loss: 0.246963, Accuracy: 90.76% -Test Set - Loss: 0.0003, Accuracy: 89.54% - -FashionMNIST: Epoch 9 - Avg Loss: 0.238650, Accuracy: 91.13% -Test Set - Loss: 0.0003, Accuracy: 89.51% - -FashionMNIST: Epoch 10 - Avg Loss: 0.229345, Accuracy: 91.46% -Test Set - Loss: 0.0003, Accuracy: 90.22% diff --git a/training_results/env1/ReLU_tr01/MNIST b/training_results/env1/ReLU_tr01/MNIST deleted file mode 100644 index f586eff..0000000 --- a/training_results/env1/ReLU_tr01/MNIST +++ /dev/null @@ -1,29 +0,0 @@ -MNIST: Epoch 1 - Avg Loss: 0.426265, Accuracy: 87.01% -Test Set - Loss: 0.0001, Accuracy: 96.91% - -MNIST: Epoch 2 - Avg Loss: 0.082446, Accuracy: 97.52% -Test Set - Loss: 0.0001, Accuracy: 98.33% - -MNIST: Epoch 3 - Avg Loss: 0.054633, Accuracy: 98.32% -Test Set - Loss: 0.0000, Accuracy: 98.62% - -MNIST: Epoch 4 - Avg Loss: 0.041592, Accuracy: 98.72% -Test Set - Loss: 0.0000, Accuracy: 98.73% - -MNIST: Epoch 5 - Avg Loss: 0.035133, Accuracy: 98.88% -Test Set - Loss: 0.0000, Accuracy: 98.81% - -MNIST: Epoch 6 - Avg Loss: 0.028988, Accuracy: 99.05% -Test Set - Loss: 0.0000, Accuracy: 98.76% - -MNIST: Epoch 7 - Avg Loss: 0.025236, Accuracy: 99.16% -Test Set - Loss: 0.0000, Accuracy: 98.58% - -MNIST: Epoch 8 - Avg Loss: 0.022040, Accuracy: 99.31% -Test Set - Loss: 0.0000, Accuracy: 98.85% - -MNIST: Epoch 9 - Avg Loss: 0.019295, Accuracy: 99.39% -Test Set - Loss: 0.0000, Accuracy: 98.94% - -MNIST: Epoch 10 - Avg Loss: 0.015332, Accuracy: 99.50% -Test Set - Loss: 0.0000, Accuracy: 98.91% 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% -- cgit v1.2.3