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assignment1-5 about cs231n HOT 7 OPEN

JinwoongKim commented on June 11, 2024

assignment1-5

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Comments (7)

JinwoongKim commented on June 11, 2024

for lr in learning_rates:
    for reg in regularization_strengths:
        svm = LinearSVM()
        svm.train(X_train_feats, y_train, learning_rate=lr, reg=reg, num_iters=1500, verbose=False)
        y_train_pred = svm.predict(X_train_feats)
        y_val_pred = svm.predict(X_val_feats)
        train_accuracy = np.mean(y_train == y_train_pred)
        val_accuracy = np.mean(y_val == y_val_pred)
        print('train accuracy : ',train_accuracy)
        print('val accuracy : ', val_accuracy)
        results[(lr,reg)] = (train_accuracy, val_accuracy)
        if val_accuracy > best_val:
            best_val = val_accuracy
            best_svm = svm
            print('best_val : ',best_val)
            print('best_svm : ',best_svm)

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JinwoongKim commented on June 11, 2024

Previous result in assign 1-2 was 0.39 !!

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JinwoongKim commented on June 11, 2024

from cs231n.

JinwoongKim commented on June 11, 2024

input_dim = X_train_feats.shape[1]
hidden_dim = 500
num_classes = 10

net = TwoLayerNet(input_dim, hidden_dim, num_classes)
best_net = None

################################################################################
# TODO: Train a two-layer neural network on image features. You may want to    #
# cross-validate various parameters as in previous sections. Store your best   #
# model in the best_net variable.                                              #
################################################################################
best_val_acc = -1

learning_rates = [0.001, 0.01, 0.1]
learning_rate_decay = [0.6, 0.7, 0.75, 0.8,0.85,0.9, 0.95]
regularization_strengths = [0.2, 0.25, 0.3, 0.35, 0.40]

for lr in learning_rates:
    for lr_d in learning_rate_decay:
        for reg in regularization_strengths:
            # Train the network
            net = TwoLayerNet(input_dim, hidden_dim, num_classes)

            stats = net.train(X_train_feats, y_train, X_val_feats, y_val,
            num_iters=1000, batch_size=200,
            learning_rate=lr, learning_rate_decay=lr_d,
            reg=reg, verbose=False)

            # Predict on the validation set
            val_acc = (net.predict(X_val_feats) == y_val).mean()
            print('Validation accuracy: ', val_acc)
        
            if val_acc > best_val_acc:
                best_val_acc = val_acc
                best_net = net
                print('best_val : ',best_val_acc)
                print('lr lrd reg : ',lr, lr_d, reg)

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JinwoongKim commented on June 11, 2024

from cs231n.

JinwoongKim commented on June 11, 2024

Validation accuracy: 0.263
lr lrd reg : 0.1 0.3 0.2
Current best accuracy: 0.263
lr lrd reg : 0.1 0.3 0.2
Validation accuracy: 0.266
lr lrd reg : 0.1 0.3 0.25
Current best accuracy: 0.266
lr lrd reg : 0.1 0.3 0.25
Validation accuracy: 0.233
lr lrd reg : 0.1 0.3 0.3
Validation accuracy: 0.254
lr lrd reg : 0.1 0.3 0.35
Validation accuracy: 0.238
lr lrd reg : 0.1 0.3 0.4
Validation accuracy: 0.229
lr lrd reg : 0.1 0.35 0.2
Validation accuracy: 0.228
lr lrd reg : 0.1 0.35 0.25
Validation accuracy: 0.217
lr lrd reg : 0.1 0.35 0.3
Validation accuracy: 0.216
lr lrd reg : 0.1 0.35 0.35
Validation accuracy: 0.206
lr lrd reg : 0.1 0.35 0.4
Validation accuracy: 0.211
lr lrd reg : 0.1 0.4 0.2
Validation accuracy: 0.21
lr lrd reg : 0.1 0.4 0.25
Validation accuracy: 0.202
lr lrd reg : 0.1 0.4 0.3
Validation accuracy: 0.204
lr lrd reg : 0.1 0.4 0.35
Validation accuracy: 0.2
lr lrd reg : 0.1 0.4 0.4
Validation accuracy: 0.202
lr lrd reg : 0.1 0.45 0.2
Validation accuracy: 0.205
lr lrd reg : 0.1 0.45 0.25
Validation accuracy: 0.196
lr lrd reg : 0.1 0.45 0.3
Validation accuracy: 0.192
lr lrd reg : 0.1 0.45 0.35
Validation accuracy: 0.192
lr lrd reg : 0.1 0.45 0.4
Validation accuracy: 0.196
lr lrd reg : 0.1 0.5 0.2
Validation accuracy: 0.196
lr lrd reg : 0.1 0.5 0.25
Validation accuracy: 0.192
lr lrd reg : 0.1 0.5 0.3
Validation accuracy: 0.189
lr lrd reg : 0.1 0.5 0.35
Validation accuracy: 0.161
lr lrd reg : 0.1 0.5 0.4
Validation accuracy: 0.196
lr lrd reg : 0.1 0.55 0.2
Validation accuracy: 0.196
lr lrd reg : 0.1 0.55 0.25
Validation accuracy: 0.189
lr lrd reg : 0.1 0.55 0.3
Validation accuracy: 0.189
lr lrd reg : 0.1 0.55 0.35
Validation accuracy: 0.189
lr lrd reg : 0.1 0.55 0.4
Validation accuracy: 0.199
lr lrd reg : 0.2 0.3 0.2
Validation accuracy: 0.202
lr lrd reg : 0.2 0.3 0.25
Validation accuracy: 0.194
lr lrd reg : 0.2 0.3 0.3
Validation accuracy: 0.193
lr lrd reg : 0.2 0.3 0.35
Validation accuracy: 0.193
lr lrd reg : 0.2 0.3 0.4
Validation accuracy: 0.196
lr lrd reg : 0.2 0.35 0.2
Validation accuracy: 0.203
lr lrd reg : 0.2 0.35 0.25
Validation accuracy: 0.189
lr lrd reg : 0.2 0.35 0.3
Validation accuracy: 0.189
lr lrd reg : 0.2 0.35 0.35
Validation accuracy: 0.193
lr lrd reg : 0.2 0.35 0.4
Validation accuracy: 0.195
lr lrd reg : 0.2 0.4 0.2
Validation accuracy: 0.192
lr lrd reg : 0.2 0.4 0.25
Validation accuracy: 0.188
lr lrd reg : 0.2 0.4 0.3
Validation accuracy: 0.188
lr lrd reg : 0.2 0.4 0.35
Validation accuracy: 0.148
lr lrd reg : 0.2 0.4 0.4
Validation accuracy: 0.193
lr lrd reg : 0.2 0.45 0.2
Validation accuracy: 0.195
lr lrd reg : 0.2 0.45 0.25
Validation accuracy: 0.188
lr lrd reg : 0.2 0.45 0.3
Validation accuracy: 0.202
lr lrd reg : 0.2 0.45 0.35
Validation accuracy: 0.071
lr lrd reg : 0.2 0.45 0.4
Validation accuracy: 0.192
lr lrd reg : 0.2 0.5 0.2
Validation accuracy: 0.196
lr lrd reg : 0.2 0.5 0.25
Validation accuracy: 0.187
lr lrd reg : 0.2 0.5 0.3
Validation accuracy: 0.183
lr lrd reg : 0.2 0.5 0.35
Validation accuracy: 0.128
lr lrd reg : 0.2 0.5 0.4
Validation accuracy: 0.192
lr lrd reg : 0.2 0.55 0.2
Validation accuracy: 0.195
lr lrd reg : 0.2 0.55 0.25
Validation accuracy: 0.187
lr lrd reg : 0.2 0.55 0.3
Validation accuracy: 0.137
lr lrd reg : 0.2 0.55 0.35
Validation accuracy: 0.112
lr lrd reg : 0.2 0.55 0.4
Validation accuracy: 0.194
lr lrd reg : 0.3 0.3 0.2
Validation accuracy: 0.195
lr lrd reg : 0.3 0.3 0.25
Validation accuracy: 0.189
lr lrd reg : 0.3 0.3 0.3
Validation accuracy: 0.188
lr lrd reg : 0.3 0.3 0.35
Validation accuracy: 0.194
lr lrd reg : 0.3 0.3 0.4
Validation accuracy: 0.193
lr lrd reg : 0.3 0.35 0.2
Validation accuracy: 0.195
lr lrd reg : 0.3 0.35 0.25
Validation accuracy: 0.188
lr lrd reg : 0.3 0.35 0.3
Validation accuracy: 0.204
lr lrd reg : 0.3 0.35 0.35
Validation accuracy: 0.082
lr lrd reg : 0.3 0.35 0.4
Validation accuracy: 0.192
lr lrd reg : 0.3 0.4 0.2
Validation accuracy: 0.195
lr lrd reg : 0.3 0.4 0.25
Validation accuracy: 0.186
lr lrd reg : 0.3 0.4 0.3
Validation accuracy: 0.182
lr lrd reg : 0.3 0.4 0.35
Validation accuracy: 0.167
lr lrd reg : 0.3 0.4 0.4
Validation accuracy: 0.194
lr lrd reg : 0.3 0.45 0.2
Validation accuracy: 0.193
lr lrd reg : 0.3 0.45 0.25
Validation accuracy: 0.188
lr lrd reg : 0.3 0.45 0.3
Validation accuracy: 0.215
lr lrd reg : 0.3 0.45 0.35
Validation accuracy: 0.117
lr lrd reg : 0.3 0.45 0.4
Validation accuracy: 0.192
lr lrd reg : 0.3 0.5 0.2
Validation accuracy: 0.195
lr lrd reg : 0.3 0.5 0.25
Validation accuracy: 0.165
lr lrd reg : 0.3 0.5 0.3
Validation accuracy: 0.139
lr lrd reg : 0.3 0.5 0.35
Validation accuracy: 0.151
lr lrd reg : 0.3 0.5 0.4
Validation accuracy: 0.193
lr lrd reg : 0.3 0.55 0.2
Validation accuracy: 0.196
lr lrd reg : 0.3 0.55 0.25
Validation accuracy: 0.19
lr lrd reg : 0.3 0.55 0.3
Validation accuracy: 0.182
lr lrd reg : 0.3 0.55 0.35
Validation accuracy: 0.198
lr lrd reg : 0.3 0.55 0.4
best_val, set : 0.266 (0.1, 0.3, 0.25)

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JinwoongKim commented on June 11, 2024

Validation accuracy: 0.299
lr lrd reg : 0.01 0.3 0.2
Current best accuracy: 0.299
lr lrd reg : 0.01 0.3 0.2
Validation accuracy: 0.326
lr lrd reg : 0.01 0.3 0.25
Current best accuracy: 0.326
lr lrd reg : 0.01 0.3 0.25
Validation accuracy: 0.338
lr lrd reg : 0.01 0.3 0.3
Current best accuracy: 0.338
lr lrd reg : 0.01 0.3 0.3
Validation accuracy: 0.305
lr lrd reg : 0.01 0.3 0.35
Validation accuracy: 0.303
lr lrd reg : 0.01 0.3 0.4
Validation accuracy: 0.318
lr lrd reg : 0.01 0.35 0.2
Validation accuracy: 0.343
lr lrd reg : 0.01 0.35 0.25
Current best accuracy: 0.343
lr lrd reg : 0.01 0.35 0.25
Validation accuracy: 0.32
lr lrd reg : 0.01 0.35 0.3
Validation accuracy: 0.332
lr lrd reg : 0.01 0.35 0.35
Validation accuracy: 0.348
lr lrd reg : 0.01 0.35 0.4
Current best accuracy: 0.348
lr lrd reg : 0.01 0.35 0.4
Validation accuracy: 0.36
lr lrd reg : 0.01 0.4 0.2
Current best accuracy: 0.36
lr lrd reg : 0.01 0.4 0.2
Validation accuracy: 0.345
lr lrd reg : 0.01 0.4 0.25
Validation accuracy: 0.33
lr lrd reg : 0.01 0.4 0.3
Validation accuracy: 0.356
lr lrd reg : 0.01 0.4 0.35
Validation accuracy: 0.327
lr lrd reg : 0.01 0.4 0.4
Validation accuracy: 0.366
lr lrd reg : 0.01 0.45 0.2
Current best accuracy: 0.366
lr lrd reg : 0.01 0.45 0.2
Validation accuracy: 0.362
lr lrd reg : 0.01 0.45 0.25
Validation accuracy: 0.379
lr lrd reg : 0.01 0.45 0.3
Current best accuracy: 0.379
lr lrd reg : 0.01 0.45 0.3
Validation accuracy: 0.352
lr lrd reg : 0.01 0.45 0.35
Validation accuracy: 0.345
lr lrd reg : 0.01 0.45 0.4
Validation accuracy: 0.364
lr lrd reg : 0.01 0.5 0.2
Validation accuracy: 0.38
lr lrd reg : 0.01 0.5 0.25
Current best accuracy: 0.38
lr lrd reg : 0.01 0.5 0.25
Validation accuracy: 0.376
lr lrd reg : 0.01 0.5 0.3
Validation accuracy: 0.352
lr lrd reg : 0.01 0.5 0.35
Validation accuracy: 0.375
lr lrd reg : 0.01 0.5 0.4
Validation accuracy: 0.394
lr lrd reg : 0.01 0.55 0.2
Current best accuracy: 0.394
lr lrd reg : 0.01 0.55 0.2
Validation accuracy: 0.374
lr lrd reg : 0.01 0.55 0.25
Validation accuracy: 0.367
lr lrd reg : 0.01 0.55 0.3
Validation accuracy: 0.376
lr lrd reg : 0.01 0.55 0.35
Validation accuracy: 0.359
lr lrd reg : 0.01 0.55 0.4
Validation accuracy: 0.383
lr lrd reg : 0.01 0.6 0.2
Validation accuracy: 0.367
lr lrd reg : 0.01 0.6 0.25
Validation accuracy: 0.367
lr lrd reg : 0.01 0.6 0.3
Validation accuracy: 0.375
lr lrd reg : 0.01 0.6 0.35
Validation accuracy: 0.387
lr lrd reg : 0.01 0.6 0.4
Validation accuracy: 0.374
lr lrd reg : 0.01 0.65 0.2
Validation accuracy: 0.405
lr lrd reg : 0.01 0.65 0.25
Current best accuracy: 0.405
lr lrd reg : 0.01 0.65 0.25
Validation accuracy: 0.352
lr lrd reg : 0.01 0.65 0.3
Validation accuracy: 0.366
lr lrd reg : 0.01 0.65 0.35
Validation accuracy: 0.368
lr lrd reg : 0.01 0.65 0.4
Validation accuracy: 0.362
lr lrd reg : 0.01 0.7 0.2
Validation accuracy: 0.374
lr lrd reg : 0.01 0.7 0.25
Validation accuracy: 0.372
lr lrd reg : 0.01 0.7 0.3
Validation accuracy: 0.354
lr lrd reg : 0.01 0.7 0.35
Validation accuracy: 0.362
lr lrd reg : 0.01 0.7 0.4
Validation accuracy: 0.368
lr lrd reg : 0.01 0.75 0.2
Validation accuracy: 0.34
lr lrd reg : 0.01 0.75 0.25
Validation accuracy: 0.374
lr lrd reg : 0.01 0.75 0.3
Validation accuracy: 0.346
lr lrd reg : 0.01 0.75 0.35
Validation accuracy: 0.381
lr lrd reg : 0.01 0.75 0.4
Validation accuracy: 0.374
lr lrd reg : 0.05 0.3 0.2
Validation accuracy: 0.356
lr lrd reg : 0.05 0.3 0.25
Validation accuracy: 0.36
lr lrd reg : 0.05 0.3 0.3
Validation accuracy: 0.358
lr lrd reg : 0.05 0.3 0.35
Validation accuracy: 0.333
lr lrd reg : 0.05 0.3 0.4
Validation accuracy: 0.324
lr lrd reg : 0.05 0.35 0.2
Validation accuracy: 0.34
lr lrd reg : 0.05 0.35 0.25
Validation accuracy: 0.335
lr lrd reg : 0.05 0.35 0.3
Validation accuracy: 0.34
lr lrd reg : 0.05 0.35 0.35
Validation accuracy: 0.326
lr lrd reg : 0.05 0.35 0.4
Validation accuracy: 0.311
lr lrd reg : 0.05 0.4 0.2
Validation accuracy: 0.31
lr lrd reg : 0.05 0.4 0.25
Validation accuracy: 0.304
lr lrd reg : 0.05 0.4 0.3
Validation accuracy: 0.308
lr lrd reg : 0.05 0.4 0.35
Validation accuracy: 0.289
lr lrd reg : 0.05 0.4 0.4
Validation accuracy: 0.268
lr lrd reg : 0.05 0.45 0.2
Validation accuracy: 0.271
lr lrd reg : 0.05 0.45 0.25
Validation accuracy: 0.264
lr lrd reg : 0.05 0.45 0.3
Validation accuracy: 0.259
lr lrd reg : 0.05 0.45 0.35
Validation accuracy: 0.248
lr lrd reg : 0.05 0.45 0.4
Validation accuracy: 0.242
lr lrd reg : 0.05 0.5 0.2
Validation accuracy: 0.246
lr lrd reg : 0.05 0.5 0.25
Validation accuracy: 0.233
lr lrd reg : 0.05 0.5 0.3
Validation accuracy: 0.236
lr lrd reg : 0.05 0.5 0.35
Validation accuracy: 0.217
lr lrd reg : 0.05 0.5 0.4
Validation accuracy: 0.226
lr lrd reg : 0.05 0.55 0.2
Validation accuracy: 0.229
lr lrd reg : 0.05 0.55 0.25
Validation accuracy: 0.211
lr lrd reg : 0.05 0.55 0.3
Validation accuracy: 0.212
lr lrd reg : 0.05 0.55 0.35
Validation accuracy: 0.209
lr lrd reg : 0.05 0.55 0.4
Validation accuracy: 0.211
lr lrd reg : 0.05 0.6 0.2
Validation accuracy: 0.213
lr lrd reg : 0.05 0.6 0.25
Validation accuracy: 0.21
lr lrd reg : 0.05 0.6 0.3
Validation accuracy: 0.196
lr lrd reg : 0.05 0.6 0.35
Validation accuracy: 0.19
lr lrd reg : 0.05 0.6 0.4
Validation accuracy: 0.207
lr lrd reg : 0.05 0.65 0.2
Validation accuracy: 0.205
lr lrd reg : 0.05 0.65 0.25
Validation accuracy: 0.203
lr lrd reg : 0.05 0.65 0.3
Validation accuracy: 0.214
lr lrd reg : 0.05 0.65 0.35
Validation accuracy: 0.193
lr lrd reg : 0.05 0.65 0.4
Validation accuracy: 0.199
lr lrd reg : 0.05 0.7 0.2
Validation accuracy: 0.201
lr lrd reg : 0.05 0.7 0.25
Validation accuracy: 0.193
lr lrd reg : 0.05 0.7 0.3
Validation accuracy: 0.19
lr lrd reg : 0.05 0.7 0.35
Validation accuracy: 0.188
lr lrd reg : 0.05 0.7 0.4
Validation accuracy: 0.197
lr lrd reg : 0.05 0.75 0.2
Validation accuracy: 0.194
lr lrd reg : 0.05 0.75 0.25
Validation accuracy: 0.189
lr lrd reg : 0.05 0.75 0.3
Validation accuracy: 0.189
lr lrd reg : 0.05 0.75 0.35
Validation accuracy: 0.198
lr lrd reg : 0.05 0.75 0.4
Validation accuracy: 0.252
lr lrd reg : 0.1 0.3 0.2
Validation accuracy: 0.25
lr lrd reg : 0.1 0.3 0.25
Validation accuracy: 0.258
lr lrd reg : 0.1 0.3 0.3
Validation accuracy: 0.236
lr lrd reg : 0.1 0.3 0.35
Validation accuracy: 0.233
lr lrd reg : 0.1 0.3 0.4
Validation accuracy: 0.228
lr lrd reg : 0.1 0.35 0.2
Validation accuracy: 0.226
lr lrd reg : 0.1 0.35 0.25
Validation accuracy: 0.223
lr lrd reg : 0.1 0.35 0.3
Validation accuracy: 0.228
lr lrd reg : 0.1 0.35 0.35
Validation accuracy: 0.214
lr lrd reg : 0.1 0.35 0.4
Validation accuracy: 0.206
lr lrd reg : 0.1 0.4 0.2
Validation accuracy: 0.217
lr lrd reg : 0.1 0.4 0.25
Validation accuracy: 0.201
lr lrd reg : 0.1 0.4 0.3
Validation accuracy: 0.199
lr lrd reg : 0.1 0.4 0.35
Validation accuracy: 0.19
lr lrd reg : 0.1 0.4 0.4
Validation accuracy: 0.206
lr lrd reg : 0.1 0.45 0.2
Validation accuracy: 0.199
lr lrd reg : 0.1 0.45 0.25
Validation accuracy: 0.198
lr lrd reg : 0.1 0.45 0.3
Validation accuracy: 0.193
lr lrd reg : 0.1 0.45 0.35
Validation accuracy: 0.19
lr lrd reg : 0.1 0.45 0.4
Validation accuracy: 0.197
lr lrd reg : 0.1 0.5 0.2
Validation accuracy: 0.196
lr lrd reg : 0.1 0.5 0.25
Validation accuracy: 0.191
lr lrd reg : 0.1 0.5 0.3
Validation accuracy: 0.19
lr lrd reg : 0.1 0.5 0.35
Validation accuracy: 0.167
lr lrd reg : 0.1 0.5 0.4
Validation accuracy: 0.195
lr lrd reg : 0.1 0.55 0.2
Validation accuracy: 0.195
lr lrd reg : 0.1 0.55 0.25
Validation accuracy: 0.191
lr lrd reg : 0.1 0.55 0.3
Validation accuracy: 0.192
lr lrd reg : 0.1 0.55 0.35
Validation accuracy: 0.191
lr lrd reg : 0.1 0.55 0.4
Validation accuracy: 0.193
lr lrd reg : 0.1 0.6 0.2
Validation accuracy: 0.195
lr lrd reg : 0.1 0.6 0.25
Validation accuracy: 0.188
lr lrd reg : 0.1 0.6 0.3
Validation accuracy: 0.197
lr lrd reg : 0.1 0.6 0.35
Validation accuracy: 0.166
lr lrd reg : 0.1 0.6 0.4
Validation accuracy: 0.194
lr lrd reg : 0.1 0.65 0.2
Validation accuracy: 0.197
lr lrd reg : 0.1 0.65 0.25
Validation accuracy: 0.186
lr lrd reg : 0.1 0.65 0.3
Validation accuracy: 0.266
lr lrd reg : 0.1 0.65 0.35
Validation accuracy: 0.08
lr lrd reg : 0.1 0.65 0.4
Validation accuracy: 0.194
lr lrd reg : 0.1 0.7 0.2
Validation accuracy: 0.195
lr lrd reg : 0.1 0.7 0.25
Validation accuracy: 0.19
lr lrd reg : 0.1 0.7 0.3
Validation accuracy: 0.24
lr lrd reg : 0.1 0.7 0.35
Validation accuracy: 0.121
lr lrd reg : 0.1 0.7 0.4
Validation accuracy: 0.191
lr lrd reg : 0.1 0.75 0.2
Validation accuracy: 0.195
lr lrd reg : 0.1 0.75 0.25
Validation accuracy: 0.186
lr lrd reg : 0.1 0.75 0.3
Validation accuracy: 0.143
lr lrd reg : 0.1 0.75 0.35
Validation accuracy: 0.107
lr lrd reg : 0.1 0.75 0.4
best_val, set : 0.405 (0.01, 0.65, 0.25)

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