xgboost early stopping tolerance

Best iteration: [5818] validation_0-mae:73.0569 validation_0-rmse:133.692 validation_1-mae:70.5473 validation_1-rmse:128.844 xgb.load: Load xgboost model from binary file; xgb.load.raw: Load serialised xgboost model from R's raw vector; xgb.model.dt.tree: Parse a boosted tree model text dump; xgboost … [6620] validation_0-mae:72.3344 validation_0-rmse:132.723 validation_1-mae:70.3581 validation_1-rmse:128.803 [7594] validation_0-mae:71.7058 validation_0-rmse:131.83 validation_1-mae:70.1965 validation_1-rmse:128.821 [6571] validation_0-mae:72.3761 validation_0-rmse:132.79 validation_1-mae:70.3679 validation_1-rmse:128.804 [6459] validation_0-mae:72.4665 validation_0-rmse:132.934 validation_1-mae:70.3899 validation_1-rmse:128.801 [7037] validation_0-mae:72.0343 validation_0-rmse:132.289 validation_1-mae:70.285 validation_1-rmse:128.82 [6460] validation_0-mae:72.4656 validation_0-rmse:132.933 validation_1-mae:70.3896 validation_1-rmse:128.801 [6187] validation_0-mae:72.7142 validation_0-rmse:133.261 validation_1-mae:70.4616 validation_1-rmse:128.811 [6729] validation_0-mae:72.2476 validation_0-rmse:132.595 validation_1-mae:70.3389 validation_1-rmse:128.809 [6414] validation_0-mae:72.5033 validation_0-rmse:132.987 validation_1-mae:70.3997 validation_1-rmse:128.801 [7238] validation_0-mae:71.9066 validation_0-rmse:132.11 validation_1-mae:70.2492 validation_1-rmse:128.815 [6559] validation_0-mae:72.386 validation_0-rmse:132.805 validation_1-mae:70.3704 validation_1-rmse:128.804 [6437] validation_0-mae:72.4839 validation_0-rmse:132.96 validation_1-mae:70.3943 validation_1-rmse:128.802 [6276] validation_0-mae:72.6321 validation_0-rmse:133.155 validation_1-mae:70.4416 validation_1-rmse:128.81 [6162] validation_0-mae:72.7375 validation_0-rmse:133.291 validation_1-mae:70.4659 validation_1-rmse:128.81 [7192] validation_0-mae:71.9342 validation_0-rmse:132.148 validation_1-mae:70.2555 validation_1-rmse:128.814 [6283] validation_0-mae:72.6254 validation_0-rmse:133.145 validation_1-mae:70.4395 validation_1-rmse:128.81 [7606] validation_0-mae:71.7001 validation_0-rmse:131.82 validation_1-mae:70.1961 validation_1-rmse:128.822 [6175] validation_0-mae:72.7254 validation_0-rmse:133.275 validation_1-mae:70.4634 validation_1-rmse:128.81 [6782] validation_0-mae:72.207 validation_0-rmse:132.536 validation_1-mae:70.3273 validation_1-rmse:128.809 [6584] validation_0-mae:72.3648 validation_0-rmse:132.771 validation_1-mae:70.3645 validation_1-rmse:128.802 [6406] validation_0-mae:72.5103 validation_0-rmse:132.998 validation_1-mae:70.4014 validation_1-rmse:128.801 [6131] validation_0-mae:72.7677 validation_0-rmse:133.333 validation_1-mae:70.4718 validation_1-rmse:128.809 In this course, you'll learn how to use this powerful library alongside pandas and scikit-learn to build and tune supervised learning models. [7546] validation_0-mae:71.7308 validation_0-rmse:131.867 validation_1-mae:70.2029 validation_1-rmse:128.818 [7078] validation_0-mae:72.0079 validation_0-rmse:132.25 validation_1-mae:70.2788 validation_1-rmse:128.821 [5870] validation_0-mae:73.0049 validation_0-rmse:133.632 validation_1-mae:70.5302 validation_1-rmse:128.832 # save the property to attributes, so they will occur in checkpoint. [7101] validation_0-mae:71.9925 validation_0-rmse:132.23 validation_1-mae:70.2734 validation_1-rmse:128.819 [5828] validation_0-mae:73.0473 validation_0-rmse:133.681 validation_1-mae:70.5445 validation_1-rmse:128.842 [6072] validation_0-mae:72.8197 validation_0-rmse:133.4 validation_1-mae:70.4825 validation_1-rmse:128.811 [6498] validation_0-mae:72.4351 validation_0-rmse:132.885 validation_1-mae:70.3813 validation_1-rmse:128.802 to your account. In fact, since its inception (early 2014), it has become the "true love" of kaggle users to deal with structured data. [7087] validation_0-mae:72.0017 validation_0-rmse:132.242 validation_1-mae:70.2767 validation_1-rmse:128.82 [6311] validation_0-mae:72.5991 validation_0-rmse:133.111 validation_1-mae:70.4299 validation_1-rmse:128.806 [6680] validation_0-mae:72.2857 validation_0-rmse:132.651 validation_1-mae:70.3472 validation_1-rmse:128.806 [6537] validation_0-mae:72.4033 validation_0-rmse:132.833 validation_1-mae:70.375 validation_1-rmse:128.805 [6733] validation_0-mae:72.2433 validation_0-rmse:132.589 validation_1-mae:70.3372 validation_1-rmse:128.808 [6432] validation_0-mae:72.4873 validation_0-rmse:132.965 validation_1-mae:70.3959 validation_1-rmse:128.804 [6062] validation_0-mae:72.8287 validation_0-rmse:133.413 validation_1-mae:70.4831 validation_1-rmse:128.809 [7206] validation_0-mae:71.9256 validation_0-rmse:132.136 validation_1-mae:70.2532 validation_1-rmse:128.814 [7094] validation_0-mae:71.9972 validation_0-rmse:132.235 validation_1-mae:70.2752 validation_1-rmse:128.821 [7481] validation_0-mae:71.7646 validation_0-rmse:131.917 validation_1-mae:70.2118 validation_1-rmse:128.817 [7022] validation_0-mae:72.0442 validation_0-rmse:132.303 validation_1-mae:70.2884 validation_1-rmse:128.821 [7583] validation_0-mae:71.7113 validation_0-rmse:131.839 validation_1-mae:70.198 validation_1-rmse:128.82 [7378] validation_0-mae:71.8225 validation_0-rmse:131.996 validation_1-mae:70.227 validation_1-rmse:128.817 [7090] validation_0-mae:71.9992 validation_0-rmse:132.239 validation_1-mae:70.2753 validation_1-rmse:128.819 [6764] validation_0-mae:72.2208 validation_0-rmse:132.555 validation_1-mae:70.3318 validation_1-rmse:128.81 [7564] validation_0-mae:71.721 validation_0-rmse:131.852 validation_1-mae:70.2004 validation_1-rmse:128.819 [7110] validation_0-mae:71.9862 validation_0-rmse:132.221 validation_1-mae:70.2712 validation_1-rmse:128.819 [7009] validation_0-mae:72.052 validation_0-rmse:132.314 validation_1-mae:70.2894 validation_1-rmse:128.819 [6331] validation_0-mae:72.5799 validation_0-rmse:133.087 validation_1-mae:70.4235 validation_1-rmse:128.805 [7492] validation_0-mae:71.7588 validation_0-rmse:131.909 validation_1-mae:70.2099 validation_1-rmse:128.817 Apologies if I'm wrong, I'll have a better look at the source and let you know. [5817] validation_0-mae:73.0579 validation_0-rmse:133.694 validation_1-mae:70.5476 validation_1-rmse:128.844 [6208] validation_0-mae:72.6957 validation_0-rmse:133.238 validation_1-mae:70.4581 validation_1-rmse:128.812 [7290] validation_0-mae:71.8746 validation_0-rmse:132.066 validation_1-mae:70.2415 validation_1-rmse:128.816 [7203] validation_0-mae:71.9271 validation_0-rmse:132.138 validation_1-mae:70.2535 validation_1-rmse:128.814 [5959] validation_0-mae:72.923 validation_0-rmse:133.53 validation_1-mae:70.5055 validation_1-rmse:128.817 [7253] validation_0-mae:71.8966 validation_0-rmse:132.098 validation_1-mae:70.2461 validation_1-rmse:128.814 [6118] validation_0-mae:72.7779 validation_0-rmse:133.345 validation_1-mae:70.4723 validation_1-rmse:128.807 [6936] validation_0-mae:72.1007 validation_0-rmse:132.385 validation_1-mae:70.3017 validation_1-rmse:128.819 [6182] validation_0-mae:72.7185 validation_0-rmse:133.267 validation_1-mae:70.4623 validation_1-rmse:128.812 [6115] validation_0-mae:72.781 validation_0-rmse:133.349 validation_1-mae:70.4736 validation_1-rmse:128.809 [6083] validation_0-mae:72.8101 validation_0-rmse:133.388 validation_1-mae:70.4798 validation_1-rmse:128.809 Can you make an example? If the number we try is too small, we need to make it larger; If the number is too large, we are wasting time to wait for the termination. 55.8s 4 [0] train-auc:0.909002 valid-auc:0.88872 Multiple eval metrics have been passed: 'valid-auc' will be used for early stopping. [6548] validation_0-mae:72.3945 validation_0-rmse:132.82 validation_1-mae:70.3729 validation_1-rmse:128.806 [6155] validation_0-mae:72.7442 validation_0-rmse:133.301 validation_1-mae:70.4671 validation_1-rmse:128.81 [6662] validation_0-mae:72.2999 validation_0-rmse:132.671 validation_1-mae:70.3505 validation_1-rmse:128.806 You may check out the related API usage on the sidebar. [7084] validation_0-mae:72.0034 validation_0-rmse:132.244 validation_1-mae:70.277 validation_1-rmse:128.82 [7493] validation_0-mae:71.7586 validation_0-rmse:131.908 validation_1-mae:70.2098 validation_1-rmse:128.816 [6531] validation_0-mae:72.4087 validation_0-rmse:132.843 validation_1-mae:70.3761 validation_1-rmse:128.805 [6654] validation_0-mae:72.3062 validation_0-rmse:132.681 validation_1-mae:70.3517 validation_1-rmse:128.805 [6244] validation_0-mae:72.6617 validation_0-rmse:133.19 validation_1-mae:70.4523 validation_1-rmse:128.816 [6743] validation_0-mae:72.2364 validation_0-rmse:132.579 validation_1-mae:70.3351 validation_1-rmse:128.808 [6110] validation_0-mae:72.784 validation_0-rmse:133.353 validation_1-mae:70.473 validation_1-rmse:128.807 [7407] validation_0-mae:71.805 validation_0-rmse:131.972 validation_1-mae:70.2223 validation_1-rmse:128.817 [6848] validation_0-mae:72.1611 validation_0-rmse:132.47 validation_1-mae:70.3168 validation_1-rmse:128.815 [7201] validation_0-mae:71.9286 validation_0-rmse:132.14 validation_1-mae:70.2539 validation_1-rmse:128.813 [6701] validation_0-mae:72.2691 validation_0-rmse:132.627 validation_1-mae:70.3441 validation_1-rmse:128.807 [7112] validation_0-mae:71.9851 validation_0-rmse:132.22 validation_1-mae:70.2706 validation_1-rmse:128.818 [7117] validation_0-mae:71.982 validation_0-rmse:132.215 validation_1-mae:70.2695 validation_1-rmse:128.817 [7387] validation_0-mae:71.8171 validation_0-rmse:131.988 validation_1-mae:70.2253 validation_1-rmse:128.817 [6805] validation_0-mae:72.1912 validation_0-rmse:132.512 validation_1-mae:70.3238 validation_1-rmse:128.812 [6750] validation_0-mae:72.2324 validation_0-rmse:132.573 validation_1-mae:70.3348 validation_1-rmse:128.809 [6823] validation_0-mae:72.1777 validation_0-rmse:132.494 validation_1-mae:70.3202 validation_1-rmse:128.812 [5745] validation_0-mae:73.1302 validation_0-rmse:133.778 validation_1-mae:70.5687 validation_1-rmse:128.859 [7272] validation_0-mae:71.8845 validation_0-rmse:132.081 validation_1-mae:70.2421 validation_1-rmse:128.813 [6913] validation_0-mae:72.1166 validation_0-rmse:132.407 validation_1-mae:70.3064 validation_1-rmse:128.819 [6812] validation_0-mae:72.1857 validation_0-rmse:132.505 validation_1-mae:70.3228 validation_1-rmse:128.812 [6870] validation_0-mae:72.1456 validation_0-rmse:132.448 validation_1-mae:70.3125 validation_1-rmse:128.816 [6963] validation_0-mae:72.083 validation_0-rmse:132.359 validation_1-mae:70.2976 validation_1-rmse:128.82 [6503] validation_0-mae:72.4309 validation_0-rmse:132.877 validation_1-mae:70.3801 validation_1-rmse:128.802 [6090] validation_0-mae:72.8036 validation_0-rmse:133.377 validation_1-mae:70.4793 validation_1-rmse:128.81 [6120] validation_0-mae:72.7764 validation_0-rmse:133.343 validation_1-mae:70.4726 validation_1-rmse:128.808 [6281] validation_0-mae:72.6273 validation_0-rmse:133.147 validation_1-mae:70.4408 validation_1-rmse:128.812 [6085] validation_0-mae:72.8083 validation_0-rmse:133.386 validation_1-mae:70.4796 validation_1-rmse:128.809 [7291] validation_0-mae:71.8738 validation_0-rmse:132.066 validation_1-mae:70.2409 validation_1-rmse:128.815 But, since the tolerance is implemented and configurable in sklearn.ensemble.GradientBoostingRegressor or in the H2OXGBoostEstimator of the h2o library, I assumed there was something similar in XGB as well. [6646] validation_0-mae:72.3127 validation_0-rmse:132.69 validation_1-mae:70.3524 validation_1-rmse:128.803 [7254] validation_0-mae:71.8958 validation_0-rmse:132.096 validation_1-mae:70.2459 validation_1-rmse:128.814 [6213] validation_0-mae:72.6909 validation_0-rmse:133.229 validation_1-mae:70.457 validation_1-rmse:128.812 Will train until valid-auc hasn't improved in 20 rounds. [6353] validation_0-mae:72.5591 validation_0-rmse:133.06 validation_1-mae:70.4167 validation_1-rmse:128.803 [7423] validation_0-mae:71.7969 validation_0-rmse:131.961 validation_1-mae:70.2213 validation_1-rmse:128.819 [6324] validation_0-mae:72.5862 validation_0-rmse:133.095 validation_1-mae:70.4259 validation_1-rmse:128.806 [6226] validation_0-mae:72.6791 validation_0-rmse:133.215 validation_1-mae:70.4547 validation_1-rmse:128.813 [7483] validation_0-mae:71.7641 validation_0-rmse:131.915 validation_1-mae:70.2117 validation_1-rmse:128.817 [6519] validation_0-mae:72.418 validation_0-rmse:132.858 validation_1-mae:70.3779 validation_1-rmse:128.803 [7447] validation_0-mae:71.7825 validation_0-rmse:131.943 validation_1-mae:70.2163 validation_1-rmse:128.817 [7377] validation_0-mae:71.8234 validation_0-rmse:131.997 validation_1-mae:70.2279 validation_1-rmse:128.818 [6208] validation_0-mae:72.6957 validation_0-rmse:133.238 validation_1-mae:70.4581 validation_1-rmse:128.812 [6258] validation_0-mae:72.6485 validation_0-rmse:133.174 validation_1-mae:70.4474 validation_1-rmse:128.813 [6932] validation_0-mae:72.103 validation_0-rmse:132.388 validation_1-mae:70.3021 validation_1-rmse:128.818 [6902] validation_0-mae:72.1237 validation_0-rmse:132.417 validation_1-mae:70.3073 validation_1-rmse:128.817 [6285] validation_0-mae:72.6234 validation_0-rmse:133.143 validation_1-mae:70.4386 validation_1-rmse:128.81 [5734] validation_0-mae:73.1422 validation_0-rmse:133.792 validation_1-mae:70.5719 validation_1-rmse:128.861 [6821] validation_0-mae:72.1791 validation_0-rmse:132.496 validation_1-mae:70.3202 validation_1-rmse:128.812 [7051] validation_0-mae:72.0249 validation_0-rmse:132.275 validation_1-mae:70.283 validation_1-rmse:128.822 [5914] validation_0-mae:72.9653 validation_0-rmse:133.584 validation_1-mae:70.5187 validation_1-rmse:128.824 [7004] validation_0-mae:72.0557 validation_0-rmse:132.319 validation_1-mae:70.2906 validation_1-rmse:128.82 [6275] validation_0-mae:72.6332 validation_0-rmse:133.157 validation_1-mae:70.4427 validation_1-rmse:128.812 [6160] validation_0-mae:72.7404 validation_0-rmse:133.296 validation_1-mae:70.4657 validation_1-rmse:128.808 [6034] validation_0-mae:72.8547 validation_0-rmse:133.446 validation_1-mae:70.4907 validation_1-rmse:128.814 [7487] validation_0-mae:71.7617 validation_0-rmse:131.913 validation_1-mae:70.2115 validation_1-rmse:128.818 [7542] validation_0-mae:71.7327 validation_0-rmse:131.87 validation_1-mae:70.2034 validation_1-rmse:128.819 [5764] validation_0-mae:73.1119 validation_0-rmse:133.757 validation_1-mae:70.5635 validation_1-rmse:128.855 [7152] validation_0-mae:71.9604 validation_0-rmse:132.183 validation_1-mae:70.2642 validation_1-rmse:128.817 build_tree_one_node: Specify whether to run on a single node. [6225] validation_0-mae:72.6794 validation_0-rmse:133.215 validation_1-mae:70.4548 validation_1-rmse:128.813 [5742] validation_0-mae:73.1339 validation_0-rmse:133.783 validation_1-mae:70.5699 validation_1-rmse:128.859 [6964] validation_0-mae:72.0821 validation_0-rmse:132.358 validation_1-mae:70.297 validation_1-rmse:128.819 Let’s describe my approach to select parameters (n_estimators, learning_rate, early_stopping_rounds) for XGBoost training. [7397] validation_0-mae:71.8116 validation_0-rmse:131.98 validation_1-mae:70.2243 validation_1-rmse:128.817 [5936] validation_0-mae:72.9437 validation_0-rmse:133.555 validation_1-mae:70.5129 validation_1-rmse:128.822 [5841] validation_0-mae:73.0341 validation_0-rmse:133.666 validation_1-mae:70.5401 validation_1-rmse:128.839 Parallel Processing : Since gradient boosting is sequential in nature it is extremely difficult to parallelize. [6147] validation_0-mae:72.7522 validation_0-rmse:133.311 validation_1-mae:70.4684 validation_1-rmse:128.809 [6875] validation_0-mae:72.1424 validation_0-rmse:132.444 validation_1-mae:70.3123 validation_1-rmse:128.816 [7265] validation_0-mae:71.8895 validation_0-rmse:132.088 validation_1-mae:70.2438 validation_1-rmse:128.814 [6036] validation_0-mae:72.8526 validation_0-rmse:133.444 validation_1-mae:70.4899 validation_1-rmse:128.813 [6041] validation_0-mae:72.8485 validation_0-rmse:133.437 validation_1-mae:70.4898 validation_1-rmse:128.814 Maximum allowed runtime in seconds for model training. [5754] validation_0-mae:73.1221 validation_0-rmse:133.768 validation_1-mae:70.5671 validation_1-rmse:128.858 [5747] validation_0-mae:73.1285 validation_0-rmse:133.777 validation_1-mae:70.5681 validation_1-rmse:128.858 [6507] validation_0-mae:72.4285 validation_0-rmse:132.873 validation_1-mae:70.3796 validation_1-rmse:128.802 [6157] validation_0-mae:72.7421 validation_0-rmse:133.298 validation_1-mae:70.4659 validation_1-rmse:128.809 [6540] validation_0-mae:72.401 validation_0-rmse:132.83 validation_1-mae:70.3746 validation_1-rmse:128.805 [7137] validation_0-mae:71.9693 validation_0-rmse:132.196 validation_1-mae:70.2662 validation_1-rmse:128.817 [6578] validation_0-mae:72.3684 validation_0-rmse:132.777 validation_1-mae:70.3661 validation_1-rmse:128.804 Relative tolerance for metric-based stopping criterion (stop if relative improvement is not at least this much) Defaults to 0.001. max_runtime_secs. [6166] validation_0-mae:72.7339 validation_0-rmse:133.286 validation_1-mae:70.465 validation_1-rmse:128.811 [6152] validation_0-mae:72.7472 validation_0-rmse:133.305 validation_1-mae:70.4679 validation_1-rmse:128.81 [6295] validation_0-mae:72.6148 validation_0-rmse:133.132 validation_1-mae:70.4354 validation_1-rmse:128.808 [6266] validation_0-mae:72.6419 validation_0-rmse:133.167 validation_1-mae:70.445 validation_1-rmse:128.812 [6167] validation_0-mae:72.7333 validation_0-rmse:133.286 validation_1-mae:70.4654 validation_1-rmse:128.811 [6287] validation_0-mae:72.6217 validation_0-rmse:133.141 validation_1-mae:70.4382 validation_1-rmse:128.81 [6211] validation_0-mae:72.692 validation_0-rmse:133.231 validation_1-mae:70.4568 validation_1-rmse:128.812 [6194] validation_0-mae:72.7083 validation_0-rmse:133.253 validation_1-mae:70.4593 validation_1-rmse:128.809 [6415] validation_0-mae:72.5023 validation_0-rmse:132.986 validation_1-mae:70.399 validation_1-rmse:128.801 [7184] validation_0-mae:71.9394 validation_0-rmse:132.156 validation_1-mae:70.2571 validation_1-rmse:128.815 [6201] validation_0-mae:72.7022 validation_0-rmse:133.246 validation_1-mae:70.4588 validation_1-rmse:128.811 [5862] validation_0-mae:73.012 validation_0-rmse:133.641 validation_1-mae:70.5308 validation_1-rmse:128.831 [6585] validation_0-mae:72.3628 validation_0-rmse:132.767 validation_1-mae:70.3639 validation_1-rmse:128.802 Fault Tolerance Theme by the Executable Book Project.rst.pdf. [5739] validation_0-mae:73.1365 validation_0-rmse:133.785 validation_1-mae:70.5707 validation_1-rmse:128.86 [6861] validation_0-mae:72.152 validation_0-rmse:132.457 validation_1-mae:70.3141 validation_1-rmse:128.815 [6029] validation_0-mae:72.8596 validation_0-rmse:133.452 validation_1-mae:70.4917 validation_1-rmse:128.815 [7021] validation_0-mae:72.045 validation_0-rmse:132.303 validation_1-mae:70.289 validation_1-rmse:128.822 [6071] validation_0-mae:72.8206 validation_0-rmse:133.401 validation_1-mae:70.4831 validation_1-rmse:128.811 [5736] validation_0-mae:73.1396 validation_0-rmse:133.789 validation_1-mae:70.5709 validation_1-rmse:128.86 [6201] validation_0-mae:72.7022 validation_0-rmse:133.246 validation_1-mae:70.4588 validation_1-rmse:128.811 [6420] validation_0-mae:72.4981 validation_0-rmse:132.981 validation_1-mae:70.3983 validation_1-rmse:128.802 [6494] validation_0-mae:72.4383 validation_0-rmse:132.889 validation_1-mae:70.3827 validation_1-rmse:128.803 [7408] validation_0-mae:71.8048 validation_0-rmse:131.972 validation_1-mae:70.2228 validation_1-rmse:128.818 [6032] validation_0-mae:72.8566 validation_0-rmse:133.449 validation_1-mae:70.4912 validation_1-rmse:128.815 These examples are extracted from open source projects. [7602] validation_0-mae:71.7019 validation_0-rmse:131.823 validation_1-mae:70.1959 validation_1-rmse:128.821 [6380] validation_0-mae:72.5343 validation_0-rmse:133.029 validation_1-mae:70.4086 validation_1-rmse:128.801 [6230] validation_0-mae:72.6748 validation_0-rmse:133.21 validation_1-mae:70.4537 validation_1-rmse:128.813 [7373] validation_0-mae:71.8254 validation_0-rmse:131.999 validation_1-mae:70.2276 validation_1-rmse:128.816 [6096] validation_0-mae:72.7978 validation_0-rmse:133.371 validation_1-mae:70.4758 validation_1-rmse:128.807 [6175] validation_0-mae:72.7254 validation_0-rmse:133.275 validation_1-mae:70.4634 validation_1-rmse:128.81 [7048] validation_0-mae:72.0262 validation_0-rmse:132.278 validation_1-mae:70.2821 validation_1-rmse:128.819 [6347] validation_0-mae:72.5646 validation_0-rmse:133.067 validation_1-mae:70.4196 validation_1-rmse:128.806 [6938] validation_0-mae:72.0993 validation_0-rmse:132.382 validation_1-mae:70.3011 validation_1-rmse:128.819 [7245] validation_0-mae:71.9018 validation_0-rmse:132.104 validation_1-mae:70.2472 validation_1-rmse:128.814 [5751] validation_0-mae:73.1244 validation_0-rmse:133.772 validation_1-mae:70.5667 validation_1-rmse:128.857 [6084] validation_0-mae:72.8091 validation_0-rmse:133.387 validation_1-mae:70.4796 validation_1-rmse:128.809 [7013] validation_0-mae:72.0502 validation_0-rmse:132.311 validation_1-mae:70.2903 validation_1-rmse:128.822