From b0acb83d9fcb19756bfdc705e171634d77a61a8a Mon Sep 17 00:00:00 2001 From: Frank Xu Date: Mon, 29 Sep 2025 10:05:35 -0400 Subject: [PATCH] fix cyfi445 lab 4 --- .../1_linear_regression_Pytorch.ipynb | 51 ++++++++++--------- 1 file changed, 26 insertions(+), 25 deletions(-) diff --git a/CYFI445/lectures/04_linear_regression_Pytorch/1_linear_regression_Pytorch.ipynb b/CYFI445/lectures/04_linear_regression_Pytorch/1_linear_regression_Pytorch.ipynb index 7d97fd7..fd1590c 100644 --- a/CYFI445/lectures/04_linear_regression_Pytorch/1_linear_regression_Pytorch.ipynb +++ b/CYFI445/lectures/04_linear_regression_Pytorch/1_linear_regression_Pytorch.ipynb @@ -19,7 +19,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 1, "id": "016485d6", "metadata": {}, "outputs": [ @@ -118,7 +118,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": null, "id": "712d00f9", "metadata": {}, "outputs": [ @@ -126,26 +126,26 @@ "name": "stdout", "output_type": "stream", "text": [ - "epoch 1: w = 0.900, b = 0.874, loss = 5.15727806\n", - "epoch 2: w = 1.001, b = 0.907, loss = 3.69042563\n", - "epoch 3: w = 1.084, b = 0.934, loss = 2.67253804\n", - "epoch 4: w = 1.154, b = 0.956, loss = 1.96617866\n", - "epoch 5: w = 1.212, b = 0.974, loss = 1.47598338\n", - "epoch 6: w = 1.260, b = 0.989, loss = 1.13578010\n", - "epoch 7: w = 1.301, b = 1.001, loss = 0.89965343\n", - "epoch 8: w = 1.335, b = 1.011, loss = 0.73574245\n", - "epoch 9: w = 1.363, b = 1.019, loss = 0.62194228\n", - "epoch 10: w = 1.387, b = 1.025, loss = 0.54291308\n", - "epoch 11: w = 1.406, b = 1.031, loss = 0.48801088\n", - "epoch 12: w = 1.423, b = 1.035, loss = 0.44985026\n", - "epoch 13: w = 1.437, b = 1.038, loss = 0.42330658\n", - "epoch 14: w = 1.448, b = 1.040, loss = 0.40482411\n", - "epoch 15: w = 1.458, b = 1.042, loss = 0.39193565\n", - "epoch 16: w = 1.466, b = 1.043, loss = 0.38292903\n", - "epoch 17: w = 1.473, b = 1.044, loss = 0.37661636\n", - "epoch 18: w = 1.479, b = 1.045, loss = 0.37217349\n", - "epoch 19: w = 1.484, b = 1.045, loss = 0.36902806\n", - "epoch 20: w = 1.488, b = 1.045, loss = 0.36678365\n" + "epoch 1: w = -0.212, b = -0.831, loss = 60.44245148\n", + "epoch 2: w = 0.140, b = -0.709, loss = 42.06572342\n", + "epoch 3: w = 0.434, b = -0.607, loss = 29.31435013\n", + "epoch 4: w = 0.678, b = -0.522, loss = 20.46628952\n", + "epoch 5: w = 0.881, b = -0.450, loss = 14.32666016\n", + "epoch 6: w = 1.051, b = -0.390, loss = 10.06634808\n", + "epoch 7: w = 1.192, b = -0.340, loss = 7.11005878\n", + "epoch 8: w = 1.309, b = -0.298, loss = 5.05860424\n", + "epoch 9: w = 1.406, b = -0.262, loss = 3.63499498\n", + "epoch 10: w = 1.487, b = -0.232, loss = 2.64703655\n", + "epoch 11: w = 1.555, b = -0.207, loss = 1.96136689\n", + "epoch 12: w = 1.611, b = -0.185, loss = 1.48545051\n", + "epoch 13: w = 1.658, b = -0.167, loss = 1.15507805\n", + "epoch 14: w = 1.696, b = -0.152, loss = 0.92569691\n", + "epoch 15: w = 1.729, b = -0.139, loss = 0.76639163\n", + "epoch 16: w = 1.755, b = -0.127, loss = 0.65571183\n", + "epoch 17: w = 1.777, b = -0.118, loss = 0.57877225\n", + "epoch 18: w = 1.796, b = -0.109, loss = 0.52524626\n", + "epoch 19: w = 1.811, b = -0.102, loss = 0.48796645\n", + "epoch 20: w = 1.823, b = -0.095, loss = 0.46196088\n" ] } ], @@ -180,7 +180,8 @@ "def train(n_iters, X, Y):\n", " for epoch in range(n_iters):\n", " y_pred = model(X) # Forward pass\n", - " l = loss(Y, y_pred) # Loss\n", + " # l = loss(Y, y_pred) # Loss\n", + " l = criterion(y_pred, Y)\n", " \n", " # Backward pass, compute autograde (directioin of change for each parameter)\n", " l.backward() \n", @@ -225,7 +226,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "09623107", "metadata": {}, "outputs": [ @@ -233,7 +234,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Prediction for x = 6: 9.973\n" + "Prediction for x = 6: 10.844\n" ] } ],