import pandas as pd | |
import numpy as np | |
from sklearn.datasets import load_wine | |
from sklearn.preprocessing import StandardScaler | |
from sklearn.pipeline import make_pipeline | |
from sklearn.cluster import KMeans | |
import matplotlib.pyplot as plt | |
import textwrap | |
import math |
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{"train_lr": 9.999999999999953e-07, "train_loss": 6.934438605865033, "epoch": 0, "n_parameters": 22050664} | |
{"train_lr": 9.999999999999953e-07, "train_loss": 6.901241369241719, "epoch": 1, "n_parameters": 22050664} | |
{"train_lr": 0.00020080000000000092, "train_loss": 6.75567844217058, "epoch": 2, "n_parameters": 22050664} | |
{"train_lr": 0.000400599999999987, "train_loss": 6.563156393744486, "epoch": 3, "n_parameters": 22050664} | |
{"train_lr": 0.0006003999999999824, "train_loss": 6.442344095543039, "epoch": 4, "n_parameters": 22050664} | |
{"train_lr": 0.0008002000000000078, "train_loss": 6.351373942064153, "epoch": 5, "n_parameters": 22050664} | |
{"train_lr": 0.0009984740801978918, "train_loss": 6.261527323656136, "epoch": 6, "n_parameters": 22050664} | |
{"train_lr": 0.0009978031724785232, "train_loss": 6.121864894787661, "epoch": 7, "n_parameters": 22050664} | |
{"train_lr": 0.0009970106729503033, "train_loss": 5.994587432947472, "epoch": 8, "n_parameters": 22050664} | |
{"train_lr": 0.0009960967771506664, "train_loss": 5.8780693907 |
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{"train_lr": 7.50000000000016e-07, "train_loss": 6.9061572715389925, "test_loss": 6.840514380356361, "test_acc1": 0.3880000025367737, "test_acc5": 1.6980000116157532, "epoch": 1, "n_parameters": 19015600} | |
{"train_lr": 0.0001506000000000007, "train_loss": 6.751336622080928, "test_loss": 6.122657075695608, "test_acc1": 2.7940000149536135, "test_acc5": 9.458000077877045, "epoch": 2, "n_parameters": 19015600} | |
{"train_lr": 0.000300450000000005, "train_loss": 6.551928960983988, "test_loss": 5.6836717786460085, "test_acc1": 5.6200000294494625, "test_acc5": 16.206000142726896, "epoch": 3, "n_parameters": 19015600} | |
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{"tra |
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{"train_lr": 2.4999999999997524e-05, "train_class_error": 81.70456260527388, "train_loss": 3.334428042000046, "train_loss_bbox": 0.8232850083237521, "train_loss_ce": 1.2169403922113597, "train_loss_giou": 1.2942026428697913, "train_cardinality_error_unscaled": 7.2747954145813605, "train_class_error_unscaled": 81.70456260527388, "train_loss_bbox_unscaled": 0.16465700167825478, "train_loss_ce_unscaled": 1.2169403922113597, "train_loss_giou_unscaled": 0.6471013214348956, "test_class_error": 68.05737717895508, "test_loss": 2.773131402587891, "test_loss_bbox": 0.6361271719932556, "test_loss_ce": 0.9216441662788392, "test_loss_giou": 1.2153600636482238, "test_cardinality_error_unscaled": 10.3104, "test_class_error_unscaled": 68.05737717895508, "test_loss_bbox_unscaled": 0.1272254345536232, "test_loss_ce_unscaled": 0.9216441662788392, "test_loss_giou_unscaled": 0.6076800318241119, "test_coco_eval_bbox": [0.025525942745533565, 0.06803296062301596, 0.01476127418922928, 0.005234962228249364, 0.01586043326641285, 0.0484 |
Annotation Type: segm | |
loading annotations into memory... | |
Done (t=2.99s) | |
creating index... | |
index created! | |
Loading and preparing results... | |
DONE (t=51.18s) | |
creating index... | |
index created! | |
evaluate category: person |
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