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fix cyfi445 lab 4

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Frank Xu
2025-09-29 10:05:35 -04:00
parent 69a0aa5308
commit b0acb83d9f
1 changed files with 26 additions and 25 deletions
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51
CYFI445/lectures/04_linear_regression_Pytorch/1_linear_regression_Pytorch.ipynb
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@@ -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"
]
}
],