From 0fe7603b6e0cb48160cc94e4a01b5f351b3c964a Mon Sep 17 00:00:00 2001
From: Jeff Heiges <jeff.heiges@colorado.edu>
Date: Wed, 5 Mar 2025 17:01:38 -0700
Subject: Training results mentioned in article
 https://jgh.xyz/posts/mnist_compare/

---
 training_results/env2/LBFGS/MNIST | 79 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 79 insertions(+)
 create mode 100644 training_results/env2/LBFGS/MNIST

(limited to 'training_results/env2/LBFGS')

diff --git a/training_results/env2/LBFGS/MNIST b/training_results/env2/LBFGS/MNIST
new file mode 100644
index 0000000..e207e43
--- /dev/null
+++ b/training_results/env2/LBFGS/MNIST
@@ -0,0 +1,79 @@
+Epoch 1 [12800/60000] Loss: 0.138132
+Epoch 1 [25600/60000] Loss: 0.053634
+Epoch 1 [38400/60000] Loss: 0.109519
+Epoch 1 [51200/60000] Loss: 0.112465
+Epoch 1 - Avg Loss: 0.233671, Accuracy: 93.28%
+
+Test Set - Loss: 0.0001, Accuracy: 97.81%
+
+Epoch 2 [12800/60000] Loss: 0.035781
+Epoch 2 [25600/60000] Loss: 0.111646
+Epoch 2 [38400/60000] Loss: 0.061600
+Epoch 2 [51200/60000] Loss: 0.120859
+Epoch 2 - Avg Loss: 0.068596, Accuracy: 98.14%
+
+Test Set - Loss: 0.0001, Accuracy: 98.02%
+
+Epoch 3 [12800/60000] Loss: 0.129996
+Epoch 3 [25600/60000] Loss: 0.069445
+Epoch 3 [38400/60000] Loss: 0.048380
+Epoch 3 [51200/60000] Loss: 0.008683
+Epoch 3 - Avg Loss: 0.055740, Accuracy: 98.53%
+
+Test Set - Loss: 0.0001, Accuracy: 98.30%
+
+Epoch 4 [12800/60000] Loss: 0.037124
+Epoch 4 [25600/60000] Loss: 0.020253
+Epoch 4 [38400/60000] Loss: 0.004947
+Epoch 4 [51200/60000] Loss: 0.048934
+Epoch 4 - Avg Loss: 0.049770, Accuracy: 98.69%
+
+Test Set - Loss: 0.0001, Accuracy: 97.85%
+
+Epoch 5 [12800/60000] Loss: 0.076356
+Epoch 5 [25600/60000] Loss: 0.046568
+Epoch 5 [38400/60000] Loss: 0.005206
+Epoch 5 [51200/60000] Loss: 0.059664
+Epoch 5 - Avg Loss: 0.044495, Accuracy: 98.85%
+
+Test Set - Loss: 0.0000, Accuracy: 98.63%
+
+Epoch 6 [12800/60000] Loss: 0.019457
+Epoch 6 [25600/60000] Loss: 0.038143
+Epoch 6 [38400/60000] Loss: 0.029849
+Epoch 6 [51200/60000] Loss: 0.038908
+Epoch 6 - Avg Loss: 0.041883, Accuracy: 98.99%
+
+Test Set - Loss: 0.0000, Accuracy: 98.61%
+
+Epoch 7 [12800/60000] Loss: 0.092034
+Epoch 7 [25600/60000] Loss: 0.022129
+Epoch 7 [38400/60000] Loss: 0.007379
+Epoch 7 [51200/60000] Loss: 0.038874
+Epoch 7 - Avg Loss: 0.037710, Accuracy: 99.00%
+
+Test Set - Loss: 0.0000, Accuracy: 98.55%
+
+Epoch 8 [12800/60000] Loss: 0.020345
+Epoch 8 [25600/60000] Loss: 0.130997
+Epoch 8 [38400/60000] Loss: 0.068181
+Epoch 8 [51200/60000] Loss: 0.023851
+Epoch 8 - Avg Loss: 0.035365, Accuracy: 99.14%
+
+Test Set - Loss: 0.0000, Accuracy: 98.78%
+
+Epoch 9 [12800/60000] Loss: 0.037697
+Epoch 9 [25600/60000] Loss: 0.019145
+Epoch 9 [38400/60000] Loss: 0.021696
+Epoch 9 [51200/60000] Loss: 0.055509
+Epoch 9 - Avg Loss: 0.033720, Accuracy: 99.21%
+
+Test Set - Loss: 0.0000, Accuracy: 98.77%
+
+Epoch 10 [12800/60000] Loss: 0.015093
+Epoch 10 [25600/60000] Loss: 0.022246
+Epoch 10 [38400/60000] Loss: 0.013344
+Epoch 10 [51200/60000] Loss: 0.006589
+Epoch 10 - Avg Loss: 0.032315, Accuracy: 99.23%
+
+Test Set - Loss: 0.0000, Accuracy: 98.74%
-- 
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