From e4e2a18606a9c950cc0d9011bba2848597f929ad Mon Sep 17 00:00:00 2001
From: Dominik Roth <dominik.roth.dev@gmail.com>
Date: Wed, 22 Sep 2021 11:09:15 +0200
Subject: [PATCH] Tweaked training params

---
 train.py | 16 +++++++++++-----
 1 file changed, 11 insertions(+), 5 deletions(-)

diff --git a/train.py b/train.py
index 4d33f32..bbcc96f 100644
--- a/train.py
+++ b/train.py
@@ -12,12 +12,12 @@ from model import Model
 def train(model, seq_len=16*64):
     tid = str(int(random.random()*99999)).zfill(5)
     print("[i] I am "+str(tid))
-    ltLoss = 50
-    lltLoss = 52
+    ltLoss = 0.75
+    lltLoss = 0.80
     model.train()
 
     criterion = nn.BCELoss()
-    optimizer = optim.Adam(model.parameters(), lr=0.0001)
+    optimizer = optim.Adam(model.parameters(), lr=0.001)
 
     state_h = [None,None]
     state_c = [None,None]
@@ -45,10 +45,16 @@ def train(model, seq_len=16*64):
 
                 correct[t] = round(y_pred.item()) == t
             ltLoss = ltLoss*0.9 + 0.1*loss.item()
-            lltLoss = lltLoss*0.9 + 0.1*ltLoss
-        print({ 'epoch': epoch, 'loss': loss.item(), 'ltLoss': ltLoss, 'ok0': correct[0], 'ok1': correct[1], 'succ': correct[0] and correct[1], 'acc': str(int(max(0, 1-math.sqrt(lltLoss))*100))+"%" })
+        lltLoss = lltLoss*0.9 + 0.1*ltLoss
+        print({ 'epoch': epoch, 'loss': loss.item(), 'lltLoss': lltLoss, 'ok0': correct[0], 'ok1': correct[1], 'succ': correct[0] and correct[1], 'acc': str(int(max(0, 1-math.sqrt(lltLoss))*100))+"%" })
         if epoch % 8 == 0:
             torch.save(model.state_dict(), 'model_savepoints/'+tid+'_'+str(epoch)+'.n')
+    if lltLoss > 0.49:
+        print("[~] My emperor! I've failed! A BARREL ROLL!")
+    elif lltLoss < 0.45:
+        print("[~] Booyaaa!!!!")
+    else:
+        print("[~] Meh...")
 
 model = Model()