{ "cells": [ { "cell_type": "markdown", "id": "c0bb1151", "metadata": { "id": "1c2a3654-8b51-4150-b16f-9a3773e26390" }, "source": [ "# Build multiclass classifiers with Amazon SageMaker linear learner to predict Risk Index per Region" ] }, { "cell_type": "code", "execution_count": 1, "id": "e4b2b716", "metadata": { "id": "0efeaf67-910c-4372-a0b0-6b37b9d24070" }, "outputs": [], "source": [ "import time\n", "st = time.time()" ] }, { "cell_type": "code", "execution_count": 2, "id": "f7db86d8", "metadata": { "id": "016491122aff46b785a056cdabb1488b" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: sagemaker in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (2.112.2)\n", "Requirement already satisfied: pandas in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from sagemaker) (1.3.4)\n", "Requirement already satisfied: schema in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from sagemaker) (0.7.5)\n", "Requirement already satisfied: pathos in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from sagemaker) (0.2.9)\n", "Requirement already satisfied: importlib-metadata<5.0,>=1.4.0 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from sagemaker) (4.8.2)\n", "Requirement already satisfied: numpy<2.0,>=1.9.0 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from sagemaker) (1.20.3)\n", "Requirement already satisfied: protobuf3-to-dict<1.0,>=0.1.5 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from sagemaker) (0.1.5)\n", "Requirement already satisfied: attrs<23,>=20.3.0 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from sagemaker) (21.2.0)\n", "Requirement already satisfied: smdebug-rulesconfig==1.0.1 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from sagemaker) (1.0.1)\n", "Requirement already satisfied: google-pasta in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from sagemaker) (0.2.0)\n", "Requirement already satisfied: packaging>=20.0 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from sagemaker) (21.3)\n", "Requirement already satisfied: protobuf<4.0,>=3.1 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from sagemaker) (3.19.1)\n", "Requirement already satisfied: boto3<2.0,>=1.20.21 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from sagemaker) (1.24.89)\n", "Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from boto3<2.0,>=1.20.21->sagemaker) (0.10.0)\n", "Requirement already satisfied: s3transfer<0.7.0,>=0.6.0 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from boto3<2.0,>=1.20.21->sagemaker) (0.6.0)\n", "Requirement already satisfied: botocore<1.28.0,>=1.27.89 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from boto3<2.0,>=1.20.21->sagemaker) (1.27.89)\n", "Requirement already satisfied: python-dateutil<3.0.0,>=2.1 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from botocore<1.28.0,>=1.27.89->boto3<2.0,>=1.20.21->sagemaker) (2.8.2)\n", "Requirement already satisfied: urllib3<1.27,>=1.25.4 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from botocore<1.28.0,>=1.27.89->boto3<2.0,>=1.20.21->sagemaker) (1.26.7)\n", "Requirement already satisfied: zipp>=0.5 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from importlib-metadata<5.0,>=1.4.0->sagemaker) (3.6.0)\n", "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from packaging>=20.0->sagemaker) (3.0.4)\n", "Requirement already satisfied: six in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from protobuf3-to-dict<1.0,>=0.1.5->sagemaker) (1.15.0)\n", "Requirement already satisfied: pytz>=2017.3 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from pandas->sagemaker) (2021.3)\n", "Requirement already satisfied: dill>=0.3.5.1 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from pathos->sagemaker) (0.3.5.1)\n", "Requirement already satisfied: ppft>=1.7.6.5 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from pathos->sagemaker) (1.7.6.5)\n", "Requirement already satisfied: multiprocess>=0.70.13 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from pathos->sagemaker) (0.70.13)\n", "Requirement already satisfied: pox>=0.3.1 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from pathos->sagemaker) (0.3.1)\n", "Requirement already satisfied: contextlib2>=0.5.5 in /opt/conda/envs/Python-3.9/lib/python3.9/site-packages (from schema->sagemaker) (21.6.0)\n" ] } ], "source": [ "!pip install sagemaker" ] }, { "cell_type": "markdown", "id": "e5e47ef7", "metadata": { "id": "9be6fde4-27a3-4df0-ac29-80e694481bda" }, "source": [ "### Import the libraries into the notebook" ] }, { "cell_type": "code", "execution_count": 3, "id": "f007c6c2", "metadata": { "id": "ab4e3b14-063c-41db-81d5-173baf52d73c" }, "outputs": [], "source": [ "%matplotlib inline\n", "import numpy as np \n", "import pandas as pd \n", "import matplotlib.pyplot as plt\n", "import ipaddress\n", "from sklearn import preprocessing\n", "import warnings\n", "warnings.filterwarnings(\"ignore\")\n", "import time\n", "import boto3\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.model_selection import train_test_split\n", "from sklearn import preprocessing\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.ensemble import RandomForestClassifier\n", "from sklearn.metrics import accuracy_score\n", "from sklearn.metrics import confusion_matrix\n", "from sklearn import metrics\n", "import seaborn as sns\n", "sns.set(style=\"white\")\n", "sns.set(style=\"whitegrid\", color_codes=True)" ] }, { "cell_type": "markdown", "id": "83bb1656", "metadata": { "id": "60c6ad98-95b7-48bb-8f4b-80b37104f116" }, "source": [ "### Update the credentials of SageMaker Access & Secret Keys" ] }, { "cell_type": "code", "execution_count": 4, "id": "7855bd03", "metadata": { "id": "8d3c2e2e-92dc-488e-af20-1d7d38c22766" }, "outputs": [], "source": [ "S3_BUCKET_REGION = \"us-east-2\"\n", "SAGEMAKER_ACCESS_KEY_ID = \"\"\n", "SAGEMAKER_SECRET_ACCESS_KEY = \"\"" ] }, { "cell_type": "markdown", "id": "5c6544f6", "metadata": { "id": "01cecc0f-b6fe-4664-9f77-e4498b0020ae" }, "source": [ "### Update the SageMaker Full Access role in the below cell" ] }, { "cell_type": "code", "execution_count": 5, "id": "45a4146b", "metadata": { "id": "f66bd626-932f-4c44-b132-b29bc5150573" }, "outputs": [], "source": [ "role=''" ] }, { "cell_type": "markdown", "id": "88ac8bdd", "metadata": { "id": "4551c425-aea9-4002-8745-dc0e39fcb12c" }, "source": [ "### Read the Risk Index per Region data as dataframe and display five records\n", "We will ingest the data files which were pre-processed in the earlier steps using the Data pre-processing Notebook" ] }, { "cell_type": "code", "execution_count": 6, "id": "a32c912f", "metadata": { "id": "aa5f1912-8e3b-4d52-a493-8c674b33bf56" }, "outputs": [ { "data": { "text/html": [ "
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DATEREGIONTotal_casesRisk_Index
02020-03-15Brussels1190
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" ], "text/plain": [ " DATE REGION Total_cases Risk_Index\n", "0 2020-03-15 Brussels 119 0\n", "1 2020-03-15 Flanders 461 2\n", "2 2020-03-15 Wallonia 383 1\n", "3 2020-03-16 Brussels 238 0\n", "4 2020-03-16 Flanders 794 2" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = pd.read_csv('https://ibm-aws-immersion-day.s3.us-east-2.amazonaws.com/publicdata/ts-data-region-RI.csv')\n", "data.head()" ] }, { "cell_type": "markdown", "id": "930336a7", "metadata": { "id": "ef4d9779-5116-4a99-98a4-443103323635" }, "source": [ "### Identify the Data Types" ] }, { "cell_type": "code", "execution_count": 7, "id": "3d0b5d91", "metadata": { "id": "258f3b6d-316f-4659-8999-445f78fd9e37" }, "outputs": [ { "data": { "text/plain": [ "DATE object\n", "REGION object\n", "Total_cases int64\n", "Risk_Index int64\n", "dtype: object" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.dtypes" ] }, { "cell_type": "markdown", "id": "7a9fc327", "metadata": { "id": "e3247dcf-e02b-4cee-9ca0-e3f1f108ee86" }, "source": [ "### Drop the Date attribute as we will not be using it" ] }, { "cell_type": "code", "execution_count": 8, "id": "b11620f7", "metadata": { "id": "72514323-cd42-4d89-b442-703a3044f87b" }, "outputs": [ { "data": { "text/html": [ "
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REGIONTotal_casesRisk_Index
0Brussels1190
1Flanders4612
2Wallonia3831
3Brussels2380
4Flanders7942
............
2215Brussels6770
2216Flanders79092
2217Wallonia13711
2218Flanders2952
2219Wallonia330
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2220 rows × 3 columns

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" ], "text/plain": [ " REGION Total_cases Risk_Index\n", "0 Brussels 119 0\n", "1 Flanders 461 2\n", "2 Wallonia 383 1\n", "3 Brussels 238 0\n", "4 Flanders 794 2\n", "... ... ... ...\n", "2215 Brussels 677 0\n", "2216 Flanders 7909 2\n", "2217 Wallonia 1371 1\n", "2218 Flanders 295 2\n", "2219 Wallonia 33 0\n", "\n", "[2220 rows x 3 columns]" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.drop('DATE', axis=1, inplace=True)\n", "data" ] }, { "cell_type": "markdown", "id": "4a62a1ba", "metadata": { "id": "bf5b3552-d60c-4a83-9e26-8e0c47f13912" }, "source": [ "### Encode the Region data into integers\n", "\n", "Brussels is encoded as 0 ::: Flanders is encoded as 1 ::: Wallonia is encoded as 2" ] }, { "cell_type": "code", "execution_count": 9, "id": "08147866", "metadata": { "id": "e1414fef-af09-41da-a021-434dea08e174" }, "outputs": [ { "data": { "text/html": [ "
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REGIONTotal_casesRisk_Index
001190
114612
223831
302380
417942
............
221506770
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2220 rows × 3 columns

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" ], "text/plain": [ " REGION Total_cases Risk_Index\n", "0 0 119 0\n", "1 1 461 2\n", "2 2 383 1\n", "3 0 238 0\n", "4 1 794 2\n", "... ... ... ...\n", "2215 0 677 0\n", "2216 1 7909 2\n", "2217 2 1371 1\n", "2218 1 295 2\n", "2219 2 33 0\n", "\n", "[2220 rows x 3 columns]" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "label_encoder = preprocessing.LabelEncoder()\n", "\n", "data['REGION']= label_encoder.fit_transform(data['REGION'])\n", "\n", "data" ] }, { "cell_type": "markdown", "id": "89d65a81", "metadata": { "id": "186346b6-2e4e-4af6-a8e8-e9ba49759229" }, "source": [ "### Convert dataframe to numpy array" ] }, { "cell_type": "code", "execution_count": 10, "id": "c29469ec", "metadata": { "id": "e3ed04af-ec6a-42be-9e4c-0111103a77fc" }, "outputs": [], "source": [ "data = data.to_numpy(dtype ='float32')" ] }, { "cell_type": "markdown", "id": "926223f6", "metadata": { "id": "c1efc710-5fa9-4d76-8ec5-d9ec7ccfc349" }, "source": [ "### Generate Data features (input) & Data Labels (target)" ] }, { "cell_type": "code", "execution_count": 11, "id": "6bb48c50", "metadata": { "id": "b2e64e76-8459-4484-8c9c-adac194265d5" }, "outputs": [], "source": [ "data_features, data_labels = data[:, :2], data[:, 2]" ] }, { "cell_type": "code", "execution_count": 12, "id": "751096e0", "metadata": { "id": "abeae90a-4761-44a1-9077-7cf0a651ab6b" }, "outputs": [ { "data": { "text/plain": [ "array([0., 2., 1., ..., 1., 2., 0.], dtype=float32)" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data_labels" ] }, { "cell_type": "markdown", "id": "2154fc24", "metadata": { "id": "855745ae-ecfd-4b09-b85a-2e567b6bc031" }, "source": [ "### Split the data into training & testing data with 80:20 ratio" ] }, { "cell_type": "code", "execution_count": 13, "id": "c7c8e574", "metadata": { "id": "3bf179b4-13fe-449e-945e-4fe0536ba0bd" }, "outputs": [], "source": [ "np.random.seed(0)\n", "train_features, test_features, train_labels, test_labels = train_test_split(\n", " data_features, data_labels, test_size=0.2)" ] }, { "cell_type": "markdown", "id": "fffcbecb", "metadata": { "id": "18a8c08c-c106-4849-a94e-36e568f596db" }, "source": [ "### Further split the test set into validation and test sets" ] }, { "cell_type": "code", "execution_count": 14, "id": "7bc30a27", "metadata": { "id": "1ba02e8a-e268-4a6b-a37a-8ebb7198b44f" }, "outputs": [], "source": [ "val_features, test_features, val_labels, test_labels = train_test_split(\n", " test_features, test_labels, test_size=0.5)" ] }, { "cell_type": "markdown", "id": "adc8e3c2", "metadata": { "id": "c2d3b26b-a345-4406-829f-5fb824231786" }, "source": [ "### Check the count of observations in features & labels" ] }, { "cell_type": "code", "execution_count": 15, "id": "751dbdfa", "metadata": { "id": "d761ae3e-27ad-4fc7-ab43-fedc27f8c288" }, "outputs": [ { "data": { "text/plain": [ "1776" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(train_features)\n", "len(train_labels)" ] }, { "cell_type": "markdown", "id": "4614f4a2", "metadata": { "id": "eb647f2c-d49d-43db-b6e4-a378fc398e1a" }, "source": [ "### Assign label names and count label frequencies" ] }, { "cell_type": "code", "execution_count": 16, "id": "b3543261", "metadata": { "id": "69196dd1-84cc-46be-8065-320542fb1722" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "label_map = {0:'Low Risk', 1:'Moderate Risk', 2:'High Risk'}\n", "label_counts = pd.DataFrame(data=train_labels)[0].map(label_map).value_counts(sort=False).sort_index(ascending=False)\n", "label_counts.plot(kind='barh', color='tomato', title='Label Counts')" ] }, { "cell_type": "code", "execution_count": 17, "id": "8eeced13", "metadata": { "id": "1d301b8c161246e68c81cbf1b0dc33fb" }, "outputs": [], "source": [ "import sagemaker\n", "session = boto3.session.Session(\n", " aws_access_key_id = SAGEMAKER_ACCESS_KEY_ID,\n", " aws_secret_access_key = SAGEMAKER_SECRET_ACCESS_KEY,\n", " region_name = S3_BUCKET_REGION\n", ")\n", "region = session.region_name\n", "sagemaker_session = sagemaker.Session(session)" ] }, { "cell_type": "code", "execution_count": 18, "id": "04ff0ebe", "metadata": { "id": "fb4b383a869b40aba899bd153b95f498" }, "outputs": [], "source": [ "import os\n", "os.environ['AWS_DEFAULT_REGION'] = S3_BUCKET_REGION\n", "os.environ['AWS_ACCESS_KEY_ID'] = SAGEMAKER_ACCESS_KEY_ID\n", "os.environ['AWS_SECRET_ACCESS_KEY'] = SAGEMAKER_SECRET_ACCESS_KEY" ] }, { "cell_type": "markdown", "id": "1222bcea", "metadata": { "id": "2dc3700a-46cb-4bdd-9a33-9656bc760fbc" }, "source": [ "## Model Building Process" ] }, { "cell_type": "markdown", "id": "ab564dd2", "metadata": { "id": "5049d185-ffdd-4f8b-aa6d-907139f9e8a0" }, "source": [ "### Instantiate the LinearLearner estimator object" ] }, { "cell_type": "code", "execution_count": 19, "id": "3c91ac8a", "metadata": { "id": "26377032-d715-4842-8b15-5108892009d2" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "train_instance_count has been renamed in sagemaker>=2.\n", "See: https://sagemaker.readthedocs.io/en/stable/v2.html for details.\n", "train_instance_type has been renamed in sagemaker>=2.\n", "See: https://sagemaker.readthedocs.io/en/stable/v2.html for details.\n" ] } ], "source": [ "import sagemaker\n", "from sagemaker.amazon.amazon_estimator import RecordSet\n", "import boto3\n", "\n", "multiclass_estimator = sagemaker.LinearLearner(role=role,\n", " train_instance_count=1,\n", " train_instance_type='ml.m4.xlarge',\n", " predictor_type='multiclass_classifier',\n", " num_classes=3)" ] }, { "cell_type": "markdown", "id": "ac515b6c", "metadata": { "id": "43b38ee9-8135-49fb-8596-dac4fa2a48b8" }, "source": [ "### Wrap data in RecordSet objects" ] }, { "cell_type": "code", "execution_count": 20, "id": "0c3e0af8", "metadata": { "id": "c5b32e30-b3e9-4a83-8151-c4a4b205cb9e" }, "outputs": [], "source": [ "train_records = multiclass_estimator.record_set(train_features, train_labels, channel='train')\n", "val_records = multiclass_estimator.record_set(val_features, val_labels, channel='validation')\n", "test_records = multiclass_estimator.record_set(test_features, test_labels, channel='test')" ] }, { "cell_type": "markdown", "id": "26c56991", "metadata": { "id": "9493026f-9070-4c2d-b15c-66c410752088" }, "source": [ "### Start a training job" ] }, { "cell_type": "code", "execution_count": 21, "id": "3770a752", "metadata": { "id": "1a23e459-b776-45bf-9e5a-78b8ea9d0c15" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2022-10-13 14:52:53 Starting - Starting the training job...\n", "2022-10-13 14:53:20 Starting - Preparing the instances for trainingProfilerReport-1665672773: InProgress\n", ".........\n", "2022-10-13 14:54:54 Downloading - Downloading input data...\n", "2022-10-13 14:55:14 Training - Downloading the training image............\n", "2022-10-13 14:57:24 Uploading - Uploading generated training model\u001b[34mDocker entrypoint called with argument(s): train\u001b[0m\n", "\u001b[34mRunning default environment configuration script\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:12 INFO 140479147329344] Reading default configuration from /opt/amazon/lib/python3.7/site-packages/algorithm/resources/default-input.json: {'mini_batch_size': '1000', 'epochs': '15', 'feature_dim': 'auto', 'use_bias': 'true', 'binary_classifier_model_selection_criteria': 'accuracy', 'f_beta': '1.0', 'target_recall': '0.8', 'target_precision': '0.8', 'num_models': 'auto', 'num_calibration_samples': '10000000', 'init_method': 'uniform', 'init_scale': '0.07', 'init_sigma': '0.01', 'init_bias': '0.0', 'optimizer': 'auto', 'loss': 'auto', 'margin': '1.0', 'quantile': '0.5', 'loss_insensitivity': '0.01', 'huber_delta': '1.0', 'num_classes': '1', 'accuracy_top_k': '3', 'wd': 'auto', 'l1': 'auto', 'momentum': 'auto', 'learning_rate': 'auto', 'beta_1': 'auto', 'beta_2': 'auto', 'bias_lr_mult': 'auto', 'bias_wd_mult': 'auto', 'use_lr_scheduler': 'true', 'lr_scheduler_step': 'auto', 'lr_scheduler_factor': 'auto', 'lr_scheduler_minimum_lr': 'auto', 'positive_example_weight_mult': '1.0', 'balance_multiclass_weights': 'false', 'normalize_data': 'true', 'normalize_label': 'auto', 'unbias_data': 'auto', 'unbias_label': 'auto', 'num_point_for_scaler': '10000', '_kvstore': 'auto', '_num_gpus': 'auto', '_num_kv_servers': 'auto', '_log_level': 'info', '_tuning_objective_metric': '', 'early_stopping_patience': '3', 'early_stopping_tolerance': '0.001', '_enable_profiler': 'false'}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:12 INFO 140479147329344] Merging with provided configuration from /opt/ml/input/config/hyperparameters.json: {'feature_dim': '2', 'mini_batch_size': '1000', 'num_classes': '3', 'predictor_type': 'multiclass_classifier'}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:12 INFO 140479147329344] Final configuration: {'mini_batch_size': '1000', 'epochs': '15', 'feature_dim': '2', 'use_bias': 'true', 'binary_classifier_model_selection_criteria': 'accuracy', 'f_beta': '1.0', 'target_recall': '0.8', 'target_precision': '0.8', 'num_models': 'auto', 'num_calibration_samples': '10000000', 'init_method': 'uniform', 'init_scale': '0.07', 'init_sigma': '0.01', 'init_bias': '0.0', 'optimizer': 'auto', 'loss': 'auto', 'margin': '1.0', 'quantile': '0.5', 'loss_insensitivity': '0.01', 'huber_delta': '1.0', 'num_classes': '3', 'accuracy_top_k': '3', 'wd': 'auto', 'l1': 'auto', 'momentum': 'auto', 'learning_rate': 'auto', 'beta_1': 'auto', 'beta_2': 'auto', 'bias_lr_mult': 'auto', 'bias_wd_mult': 'auto', 'use_lr_scheduler': 'true', 'lr_scheduler_step': 'auto', 'lr_scheduler_factor': 'auto', 'lr_scheduler_minimum_lr': 'auto', 'positive_example_weight_mult': '1.0', 'balance_multiclass_weights': 'false', 'normalize_data': 'true', 'normalize_label': 'auto', 'unbias_data': 'auto', 'unbias_label': 'auto', 'num_point_for_scaler': '10000', '_kvstore': 'auto', '_num_gpus': 'auto', '_num_kv_servers': 'auto', '_log_level': 'info', '_tuning_objective_metric': '', 'early_stopping_patience': '3', 'early_stopping_tolerance': '0.001', '_enable_profiler': 'false', 'predictor_type': 'multiclass_classifier'}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:16 WARNING 140479147329344] Loggers have already been setup.\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:16 INFO 140479147329344] Final configuration: {'mini_batch_size': '1000', 'epochs': '15', 'feature_dim': '2', 'use_bias': 'true', 'binary_classifier_model_selection_criteria': 'accuracy', 'f_beta': '1.0', 'target_recall': '0.8', 'target_precision': '0.8', 'num_models': 'auto', 'num_calibration_samples': '10000000', 'init_method': 'uniform', 'init_scale': '0.07', 'init_sigma': '0.01', 'init_bias': '0.0', 'optimizer': 'auto', 'loss': 'auto', 'margin': '1.0', 'quantile': '0.5', 'loss_insensitivity': '0.01', 'huber_delta': '1.0', 'num_classes': '3', 'accuracy_top_k': '3', 'wd': 'auto', 'l1': 'auto', 'momentum': 'auto', 'learning_rate': 'auto', 'beta_1': 'auto', 'beta_2': 'auto', 'bias_lr_mult': 'auto', 'bias_wd_mult': 'auto', 'use_lr_scheduler': 'true', 'lr_scheduler_step': 'auto', 'lr_scheduler_factor': 'auto', 'lr_scheduler_minimum_lr': 'auto', 'positive_example_weight_mult': '1.0', 'balance_multiclass_weights': 'false', 'normalize_data': 'true', 'normalize_label': 'auto', 'unbias_data': 'auto', 'unbias_label': 'auto', 'num_point_for_scaler': '10000', '_kvstore': 'auto', '_num_gpus': 'auto', '_num_kv_servers': 'auto', '_log_level': 'info', '_tuning_objective_metric': '', 'early_stopping_patience': '3', 'early_stopping_tolerance': '0.001', '_enable_profiler': 'false', 'predictor_type': 'multiclass_classifier'}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:16 WARNING 140479147329344] Loggers have already been setup.\u001b[0m\n", "\u001b[34mProcess 1 is a worker.\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:16 INFO 140479147329344] Using default worker.\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:16 INFO 140479147329344] Checkpoint loading and saving are disabled.\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:16.724] [tensorio] [warning] TensorIO is already initialized; ignoring the initialization routine.\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:16.725] [tensorio] [warning] TensorIO is already initialized; ignoring the initialization routine.\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:16.755] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 0, \"duration\": 33, \"num_examples\": 1, \"num_bytes\": 52000}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:16 INFO 140479147329344] Create Store: local\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:16.785] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 1, \"duration\": 28, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:16 INFO 140479147329344] Scaler algorithm parameters\n", " \u001b[0m\n", "\u001b[34m[10/13/2022 14:57:16 INFO 140479147329344] Scaling model computed with parameters:\n", " {'stdev_label': None, 'stdev_weight': \u001b[0m\n", "\u001b[34m[8.0769736e-01 4.2531353e+03]\u001b[0m\n", "\u001b[34m, 'mean_label': None, 'mean_weight': \u001b[0m\n", "\u001b[34m[9.750000e-01 2.589306e+03]\u001b[0m\n", "\u001b[34m}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:16 INFO 140479147329344] nvidia-smi: took 0.032 seconds to run.\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:16 INFO 140479147329344] nvidia-smi identified 0 GPUs.\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:16 INFO 140479147329344] Number of GPUs being used: 0\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673036.9105487, \"EndTime\": 1665673036.910585, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"Meta\": \"init_train_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 2776.0, \"count\": 1, \"min\": 2776, \"max\": 2776}, \"Total Batches Seen\": {\"sum\": 3.0, \"count\": 1, \"min\": 3, \"max\": 3}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Number of Records Since Last Reset\": {\"sum\": 0.0, \"count\": 1, \"min\": 0, \"max\": 0}, \"Number of Batches Since Last Reset\": {\"sum\": 0.0, \"count\": 1, \"min\": 0, \"max\": 0}}}\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:16.985] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 4, \"duration\": 74, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673036.9854827, \"EndTime\": 1665673036.9855692, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 0}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0954010009765625, \"count\": 1, \"min\": 1.0954010009765625, \"max\": 1.0954010009765625}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673036.9856544, \"EndTime\": 1665673036.985672, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 1}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0995819091796875, \"count\": 1, \"min\": 1.0995819091796875, \"max\": 1.0995819091796875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673036.9857838, \"EndTime\": 1665673036.9858246, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 2}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.1139429931640625, \"count\": 1, \"min\": 1.1139429931640625, \"max\": 1.1139429931640625}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673036.985883, \"EndTime\": 1665673036.985898, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 3}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.06709375, \"count\": 1, \"min\": 1.06709375, \"max\": 1.06709375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673036.9859438, \"EndTime\": 1665673036.9859552, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 4}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.1328526611328125, \"count\": 1, \"min\": 1.1328526611328125, \"max\": 1.1328526611328125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673036.9860282, \"EndTime\": 1665673036.9860435, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 5}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0979373779296875, \"count\": 1, \"min\": 1.0979373779296875, \"max\": 1.0979373779296875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673036.986086, \"EndTime\": 1665673036.9860969, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 6}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0733134765625, \"count\": 1, \"min\": 1.0733134765625, \"max\": 1.0733134765625}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673036.9861677, \"EndTime\": 1665673036.9861836, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 7}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.101536376953125, \"count\": 1, \"min\": 1.101536376953125, \"max\": 1.101536376953125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673036.9862292, \"EndTime\": 1665673036.9862406, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 8}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.1102474365234376, \"count\": 1, \"min\": 1.1102474365234376, \"max\": 1.1102474365234376}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673036.986279, \"EndTime\": 1665673036.9862895, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 9}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.123679443359375, \"count\": 1, \"min\": 1.123679443359375, \"max\": 1.123679443359375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673036.986382, \"EndTime\": 1665673036.9863977, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 10}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0930557861328125, \"count\": 1, \"min\": 1.0930557861328125, \"max\": 1.0930557861328125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673036.9864714, \"EndTime\": 1665673036.9865131, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 11}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.100878662109375, \"count\": 1, \"min\": 1.100878662109375, \"max\": 1.100878662109375}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:16 INFO 140479147329344] #quality_metric: host=algo-1, epoch=0, train multiclass_cross_entropy_objective =1.0954010009765625\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.000] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 0, \"duration\": 275, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.015] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 2, \"duration\": 14, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0193179, \"EndTime\": 1665673037.0193799, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 0}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0870965493691933, \"count\": 1, \"min\": 1.0870965493691933, \"max\": 1.0870965493691933}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0194638, \"EndTime\": 1665673037.0194852, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 1}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0952040526244018, \"count\": 1, \"min\": 1.0952040526244018, \"max\": 1.0952040526244018}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0195482, \"EndTime\": 1665673037.0195668, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 2}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.1503361882390202, \"count\": 1, \"min\": 1.1503361882390202, \"max\": 1.1503361882390202}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0198133, \"EndTime\": 1665673037.0198379, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 3}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0671759940482475, \"count\": 1, \"min\": 1.0671759940482475, \"max\": 1.0671759940482475}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0198998, \"EndTime\": 1665673037.0199862, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 4}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.111834276903857, \"count\": 1, \"min\": 1.111834276903857, \"max\": 1.111834276903857}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0200992, \"EndTime\": 1665673037.0201216, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 5}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.053416277911212, \"count\": 1, \"min\": 1.053416277911212, \"max\": 1.053416277911212}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0201793, \"EndTime\": 1665673037.0202537, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 6}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9854361731726844, \"count\": 1, \"min\": 0.9854361731726844, \"max\": 0.9854361731726844}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0203767, \"EndTime\": 1665673037.0203993, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 7}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.092049332352372, \"count\": 1, \"min\": 1.092049332352372, \"max\": 1.092049332352372}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0205162, \"EndTime\": 1665673037.0205324, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 8}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0225276775188274, \"count\": 1, \"min\": 1.0225276775188274, \"max\": 1.0225276775188274}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0205696, \"EndTime\": 1665673037.02058, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 9}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 3.2381616540857263, \"count\": 1, \"min\": 3.2381616540857263, \"max\": 3.2381616540857263}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0207047, \"EndTime\": 1665673037.0207312, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 10}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0837469702368383, \"count\": 1, \"min\": 1.0837469702368383, \"max\": 1.0837469702368383}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0208294, \"EndTime\": 1665673037.020843, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"model\": 11}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.9163554423564189, \"count\": 1, \"min\": 1.9163554423564189, \"max\": 1.9163554423564189}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=0, validation multiclass_cross_entropy_objective =1.0870965493691933\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=0, criteria=multiclass_cross_entropy_objective, value=0.9854361731726844\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Epoch 0: Loss improved. Updating best model\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saving model for epoch: 0\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saved checkpoint to \"/tmp/tmpl9kr4k38/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #progress_metric: host=algo-1, completed 6.666666666666667 % of epochs\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673036.9108946, \"EndTime\": 1665673037.036275, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 0, \"Meta\": \"training_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 4552.0, \"count\": 1, \"min\": 4552, \"max\": 4552}, \"Total Batches Seen\": {\"sum\": 5.0, \"count\": 1, \"min\": 5, \"max\": 5}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 3.0, \"count\": 1, \"min\": 3, \"max\": 3}, \"Number of Records Since Last Reset\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Number of Batches Since Last Reset\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #throughput_metric: host=algo-1, train throughput=14120.95068243858 records/second\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.067] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 6, \"duration\": 30, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0674202, \"EndTime\": 1665673037.0674796, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 0}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.086185791015625, \"count\": 1, \"min\": 1.086185791015625, \"max\": 1.086185791015625}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.067563, \"EndTime\": 1665673037.067585, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 1}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.09255615234375, \"count\": 1, \"min\": 1.09255615234375, \"max\": 1.09255615234375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0676508, \"EndTime\": 1665673037.0676715, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 2}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.1436983642578125, \"count\": 1, \"min\": 1.1436983642578125, \"max\": 1.1436983642578125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0677311, \"EndTime\": 1665673037.0677497, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 3}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.06668115234375, \"count\": 1, \"min\": 1.06668115234375, \"max\": 1.06668115234375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.067806, \"EndTime\": 1665673037.0678241, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 4}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.109125, \"count\": 1, \"min\": 1.109125, \"max\": 1.109125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0678797, \"EndTime\": 1665673037.067897, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 5}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0555576171875, \"count\": 1, \"min\": 1.0555576171875, \"max\": 1.0555576171875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0679533, \"EndTime\": 1665673037.067971, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 6}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9857898559570313, \"count\": 1, \"min\": 0.9857898559570313, \"max\": 0.9857898559570313}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.068025, \"EndTime\": 1665673037.0680423, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 7}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.091218017578125, \"count\": 1, \"min\": 1.091218017578125, \"max\": 1.091218017578125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0680952, \"EndTime\": 1665673037.0681133, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 8}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0247166748046874, \"count\": 1, \"min\": 1.0247166748046874, \"max\": 1.0247166748046874}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0681677, \"EndTime\": 1665673037.0681856, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 9}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 3.1880087890625, \"count\": 1, \"min\": 3.1880087890625, \"max\": 3.1880087890625}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0682416, \"EndTime\": 1665673037.0682588, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 10}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0830186767578125, \"count\": 1, \"min\": 1.0830186767578125, \"max\": 1.0830186767578125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0683138, \"EndTime\": 1665673037.0683312, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 11}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.89115087890625, \"count\": 1, \"min\": 1.89115087890625, \"max\": 1.89115087890625}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=1, train multiclass_cross_entropy_objective =1.086185791015625\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.092] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 5, \"duration\": 13, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0950146, \"EndTime\": 1665673037.095047, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 0}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0596500431095157, \"count\": 1, \"min\": 1.0596500431095157, \"max\": 1.0596500431095157}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0951114, \"EndTime\": 1665673037.0951314, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 1}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0570338481181376, \"count\": 1, \"min\": 1.0570338481181376, \"max\": 1.0570338481181376}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.095214, \"EndTime\": 1665673037.095237, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 2}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0374676128765483, \"count\": 1, \"min\": 1.0374676128765483, \"max\": 1.0374676128765483}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.095299, \"EndTime\": 1665673037.0953186, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 3}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0151929425763655, \"count\": 1, \"min\": 1.0151929425763655, \"max\": 1.0151929425763655}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.095376, \"EndTime\": 1665673037.0953934, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 4}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0885723217113599, \"count\": 1, \"min\": 1.0885723217113599, \"max\": 1.0885723217113599}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0954502, \"EndTime\": 1665673037.095467, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 5}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0263055337441933, \"count\": 1, \"min\": 1.0263055337441933, \"max\": 1.0263055337441933}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0955276, \"EndTime\": 1665673037.0955458, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 6}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9337130709811374, \"count\": 1, \"min\": 0.9337130709811374, \"max\": 0.9337130709811374}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0956113, \"EndTime\": 1665673037.0956311, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 7}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0735106597075592, \"count\": 1, \"min\": 1.0735106597075592, \"max\": 1.0735106597075592}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0956974, \"EndTime\": 1665673037.095715, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 8}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9513241879574887, \"count\": 1, \"min\": 0.9513241879574887, \"max\": 0.9513241879574887}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0957716, \"EndTime\": 1665673037.0957901, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 9}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7848566416147593, \"count\": 1, \"min\": 0.7848566416147593, \"max\": 0.7848566416147593}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0958455, \"EndTime\": 1665673037.095862, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 10}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0707135587125212, \"count\": 1, \"min\": 1.0707135587125212, \"max\": 1.0707135587125212}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0959175, \"EndTime\": 1665673037.0959353, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"model\": 11}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8712932139903575, \"count\": 1, \"min\": 0.8712932139903575, \"max\": 0.8712932139903575}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=1, validation multiclass_cross_entropy_objective =1.0596500431095157\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=1, criteria=multiclass_cross_entropy_objective, value=0.7848566416147593\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Epoch 1: Loss improved. Updating best model\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saving model for epoch: 1\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saved checkpoint to \"/tmp/tmpqvxm7kou/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #progress_metric: host=algo-1, completed 13.333333333333334 % of epochs\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.0369997, \"EndTime\": 1665673037.1076698, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 1, \"Meta\": \"training_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 6328.0, \"count\": 1, \"min\": 6328, \"max\": 6328}, \"Total Batches Seen\": {\"sum\": 7.0, \"count\": 1, \"min\": 7, \"max\": 7}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 4.0, \"count\": 1, \"min\": 4, \"max\": 4}, \"Number of Records Since Last Reset\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Number of Batches Since Last Reset\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #throughput_metric: host=algo-1, train throughput=25077.290996313688 records/second\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.130] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 8, \"duration\": 21, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1301048, \"EndTime\": 1665673037.1301558, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 0}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0606181640625, \"count\": 1, \"min\": 1.0606181640625, \"max\": 1.0606181640625}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1302195, \"EndTime\": 1665673037.1302392, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 1}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0572132568359376, \"count\": 1, \"min\": 1.0572132568359376, \"max\": 1.0572132568359376}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1303, \"EndTime\": 1665673037.1303184, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 2}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0368223876953124, \"count\": 1, \"min\": 1.0368223876953124, \"max\": 1.0368223876953124}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1303756, \"EndTime\": 1665673037.1303937, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 3}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.01776220703125, \"count\": 1, \"min\": 1.01776220703125, \"max\": 1.01776220703125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1304486, \"EndTime\": 1665673037.1304657, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 4}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.087057373046875, \"count\": 1, \"min\": 1.087057373046875, \"max\": 1.087057373046875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1305199, \"EndTime\": 1665673037.1305368, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 5}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0293048095703126, \"count\": 1, \"min\": 1.0293048095703126, \"max\": 1.0293048095703126}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1305895, \"EndTime\": 1665673037.1306067, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 6}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9412068481445313, \"count\": 1, \"min\": 0.9412068481445313, \"max\": 0.9412068481445313}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.13066, \"EndTime\": 1665673037.1306767, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 7}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.07357568359375, \"count\": 1, \"min\": 1.07357568359375, \"max\": 1.07357568359375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.130729, \"EndTime\": 1665673037.1307456, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 8}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9560392456054687, \"count\": 1, \"min\": 0.9560392456054687, \"max\": 0.9560392456054687}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1307979, \"EndTime\": 1665673037.1308153, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 9}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8069232788085937, \"count\": 1, \"min\": 0.8069232788085937, \"max\": 0.8069232788085937}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.130871, \"EndTime\": 1665673037.1309292, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 10}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.070302490234375, \"count\": 1, \"min\": 1.070302490234375, \"max\": 1.070302490234375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1309974, \"EndTime\": 1665673037.1310174, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 11}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8821119995117187, \"count\": 1, \"min\": 0.8821119995117187, \"max\": 0.8821119995117187}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=2, train multiclass_cross_entropy_objective =1.0606181640625\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.157] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 8, \"duration\": 15, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1617007, \"EndTime\": 1665673037.1617508, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 0}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0409196733354449, \"count\": 1, \"min\": 1.0409196733354449, \"max\": 1.0409196733354449}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1618392, \"EndTime\": 1665673037.1618867, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 1}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0350620166675464, \"count\": 1, \"min\": 1.0350620166675464, \"max\": 1.0350620166675464}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.161952, \"EndTime\": 1665673037.16197, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 2}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0066045812658362, \"count\": 1, \"min\": 1.0066045812658362, \"max\": 1.0066045812658362}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1620345, \"EndTime\": 1665673037.1620696, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 3}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9919012258718679, \"count\": 1, \"min\": 0.9919012258718679, \"max\": 0.9919012258718679}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1621537, \"EndTime\": 1665673037.1621718, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 4}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0670623091964033, \"count\": 1, \"min\": 1.0670623091964033, \"max\": 1.0670623091964033}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1622238, \"EndTime\": 1665673037.1622388, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 5}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0052759668848537, \"count\": 1, \"min\": 1.0052759668848537, \"max\": 1.0052759668848537}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1623237, \"EndTime\": 1665673037.1623423, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 6}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9063583236556869, \"count\": 1, \"min\": 0.9063583236556869, \"max\": 0.9063583236556869}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1624324, \"EndTime\": 1665673037.16245, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 7}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.05790545489337, \"count\": 1, \"min\": 1.05790545489337, \"max\": 1.05790545489337}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1624992, \"EndTime\": 1665673037.162514, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 8}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8919179418065526, \"count\": 1, \"min\": 0.8919179418065526, \"max\": 0.8919179418065526}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1625996, \"EndTime\": 1665673037.1626177, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 9}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9264925020235079, \"count\": 1, \"min\": 0.9264925020235079, \"max\": 0.9264925020235079}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1626973, \"EndTime\": 1665673037.162716, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 10}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0575632318720087, \"count\": 1, \"min\": 1.0575632318720087, \"max\": 1.0575632318720087}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1627705, \"EndTime\": 1665673037.1627853, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"model\": 11}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8339095931869369, \"count\": 1, \"min\": 0.8339095931869369, \"max\": 0.8339095931869369}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=2, validation multiclass_cross_entropy_objective =1.0409196733354449\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=2, criteria=multiclass_cross_entropy_objective, value=0.8339095931869369\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saving model for epoch: 2\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saved checkpoint to \"/tmp/tmpqdl7f42x/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #progress_metric: host=algo-1, completed 20.0 % of epochs\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1079922, \"EndTime\": 1665673037.1731956, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 2, \"Meta\": \"training_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 8104.0, \"count\": 1, \"min\": 8104, \"max\": 8104}, \"Total Batches Seen\": {\"sum\": 9.0, \"count\": 1, \"min\": 9, \"max\": 9}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 5.0, \"count\": 1, \"min\": 5, \"max\": 5}, \"Number of Records Since Last Reset\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Number of Batches Since Last Reset\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #throughput_metric: host=algo-1, train throughput=27192.0943553951 records/second\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.195] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 10, \"duration\": 21, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1956062, \"EndTime\": 1665673037.1956658, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 0}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0444185791015625, \"count\": 1, \"min\": 1.0444185791015625, \"max\": 1.0444185791015625}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1957471, \"EndTime\": 1665673037.1957688, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 1}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0386099853515625, \"count\": 1, \"min\": 1.0386099853515625, \"max\": 1.0386099853515625}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1958308, \"EndTime\": 1665673037.195851, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 2}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0124017333984374, \"count\": 1, \"min\": 1.0124017333984374, \"max\": 1.0124017333984374}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1959083, \"EndTime\": 1665673037.1959264, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 3}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.997985595703125, \"count\": 1, \"min\": 0.997985595703125, \"max\": 0.997985595703125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1959848, \"EndTime\": 1665673037.196002, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 4}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.06651123046875, \"count\": 1, \"min\": 1.06651123046875, \"max\": 1.06651123046875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1960561, \"EndTime\": 1665673037.1960728, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 5}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0092876586914064, \"count\": 1, \"min\": 1.0092876586914064, \"max\": 1.0092876586914064}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1961255, \"EndTime\": 1665673037.1961432, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 6}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.91410498046875, \"count\": 1, \"min\": 0.91410498046875, \"max\": 0.91410498046875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1961966, \"EndTime\": 1665673037.1962137, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 7}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.05976513671875, \"count\": 1, \"min\": 1.05976513671875, \"max\": 1.05976513671875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1962674, \"EndTime\": 1665673037.1962836, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 8}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8989544677734375, \"count\": 1, \"min\": 0.8989544677734375, \"max\": 0.8989544677734375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1963367, \"EndTime\": 1665673037.1963542, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 9}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9466784057617188, \"count\": 1, \"min\": 0.9466784057617188, \"max\": 0.9466784057617188}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1964073, \"EndTime\": 1665673037.1964235, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 10}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0585916748046875, \"count\": 1, \"min\": 1.0585916748046875, \"max\": 1.0585916748046875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1964834, \"EndTime\": 1665673037.1964998, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 11}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8438983764648438, \"count\": 1, \"min\": 0.8438983764648438, \"max\": 0.8438983764648438}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=3, train multiclass_cross_entropy_objective =1.0444185791015625\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.219] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 11, \"duration\": 9, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.223013, \"EndTime\": 1665673037.2230463, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 0}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0270592629372537, \"count\": 1, \"min\": 1.0270592629372537, \"max\": 1.0270592629372537}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.223125, \"EndTime\": 1665673037.2231462, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 1}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.019809963466885, \"count\": 1, \"min\": 1.019809963466885, \"max\": 1.019809963466885}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2232394, \"EndTime\": 1665673037.2232594, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 2}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9941092138891822, \"count\": 1, \"min\": 0.9941092138891822, \"max\": 0.9941092138891822}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2233179, \"EndTime\": 1665673037.2233343, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 3}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9777897327869862, \"count\": 1, \"min\": 0.9777897327869862, \"max\": 0.9777897327869862}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2233894, \"EndTime\": 1665673037.2234075, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 4}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.046907510843363, \"count\": 1, \"min\": 1.046907510843363, \"max\": 1.046907510843363}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2234972, \"EndTime\": 1665673037.223518, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 5}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9883912232545045, \"count\": 1, \"min\": 0.9883912232545045, \"max\": 0.9883912232545045}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2235768, \"EndTime\": 1665673037.2235932, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 6}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.886699779613598, \"count\": 1, \"min\": 0.886699779613598, \"max\": 0.886699779613598}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2236483, \"EndTime\": 1665673037.2236645, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 7}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0451556368991062, \"count\": 1, \"min\": 1.0451556368991062, \"max\": 1.0451556368991062}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2237196, \"EndTime\": 1665673037.223738, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 8}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8441734657631265, \"count\": 1, \"min\": 0.8441734657631265, \"max\": 0.8441734657631265}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.223792, \"EndTime\": 1665673037.2238092, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 9}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 2.0304856858811937, \"count\": 1, \"min\": 2.0304856858811937, \"max\": 2.0304856858811937}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2238646, \"EndTime\": 1665673037.2238822, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 10}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.045929917344102, \"count\": 1, \"min\": 1.045929917344102, \"max\": 1.045929917344102}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2239358, \"EndTime\": 1665673037.2239525, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"model\": 11}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8418076661255982, \"count\": 1, \"min\": 0.8418076661255982, \"max\": 0.8418076661255982}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=3, validation multiclass_cross_entropy_objective =1.0270592629372537\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=3, criteria=multiclass_cross_entropy_objective, value=0.8418076661255982\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saving model for epoch: 3\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saved checkpoint to \"/tmp/tmpc4_djjpe/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #progress_metric: host=algo-1, completed 26.666666666666668 % of epochs\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.1734161, \"EndTime\": 1665673037.231262, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 3, \"Meta\": \"training_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 9880.0, \"count\": 1, \"min\": 9880, \"max\": 9880}, \"Total Batches Seen\": {\"sum\": 11.0, \"count\": 1, \"min\": 11, \"max\": 11}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 6.0, \"count\": 1, \"min\": 6, \"max\": 6}, \"Number of Records Since Last Reset\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Number of Batches Since Last Reset\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #throughput_metric: host=algo-1, train throughput=30625.049454231503 records/second\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.265] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 12, \"duration\": 33, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.265497, \"EndTime\": 1665673037.265551, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 0}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.03218310546875, \"count\": 1, \"min\": 1.03218310546875, \"max\": 1.03218310546875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2656631, \"EndTime\": 1665673037.2656875, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 1}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0253536376953125, \"count\": 1, \"min\": 1.0253536376953125, \"max\": 1.0253536376953125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2657533, \"EndTime\": 1665673037.2657707, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 2}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.00282861328125, \"count\": 1, \"min\": 1.00282861328125, \"max\": 1.00282861328125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.265858, \"EndTime\": 1665673037.265933, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 3}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9858480224609375, \"count\": 1, \"min\": 0.9858480224609375, \"max\": 0.9858480224609375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2660031, \"EndTime\": 1665673037.2660196, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 4}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.047233154296875, \"count\": 1, \"min\": 1.047233154296875, \"max\": 1.047233154296875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2661057, \"EndTime\": 1665673037.2661242, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 5}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9927888793945312, \"count\": 1, \"min\": 0.9927888793945312, \"max\": 0.9927888793945312}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2661777, \"EndTime\": 1665673037.2661917, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 6}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8956713256835938, \"count\": 1, \"min\": 0.8956713256835938, \"max\": 0.8956713256835938}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2662394, \"EndTime\": 1665673037.266255, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 7}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0487437744140624, \"count\": 1, \"min\": 1.0487437744140624, \"max\": 1.0487437744140624}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2663043, \"EndTime\": 1665673037.2663188, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 8}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8530120849609375, \"count\": 1, \"min\": 0.8530120849609375, \"max\": 0.8530120849609375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2663658, \"EndTime\": 1665673037.266379, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 9}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 2.03142626953125, \"count\": 1, \"min\": 2.03142626953125, \"max\": 2.03142626953125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2664273, \"EndTime\": 1665673037.2664459, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 10}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0487557373046874, \"count\": 1, \"min\": 1.0487557373046874, \"max\": 1.0487557373046874}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.266495, \"EndTime\": 1665673037.2665093, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 11}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8513424072265625, \"count\": 1, \"min\": 0.8513424072265625, \"max\": 0.8513424072265625}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=4, train multiclass_cross_entropy_objective =1.03218310546875\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.297] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 14, \"duration\": 16, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.302516, \"EndTime\": 1665673037.302567, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 0}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0100545109929264, \"count\": 1, \"min\": 1.0100545109929264, \"max\": 1.0100545109929264}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3026574, \"EndTime\": 1665673037.3032525, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 1}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9982991261525197, \"count\": 1, \"min\": 0.9982991261525197, \"max\": 0.9982991261525197}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.303326, \"EndTime\": 1665673037.3034856, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 2}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9440632725621129, \"count\": 1, \"min\": 0.9440632725621129, \"max\": 0.9440632725621129}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.303571, \"EndTime\": 1665673037.3037276, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 3}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9517125310124578, \"count\": 1, \"min\": 0.9517125310124578, \"max\": 0.9517125310124578}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3038092, \"EndTime\": 1665673037.3039432, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 4}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0277523006404843, \"count\": 1, \"min\": 1.0277523006404843, \"max\": 1.0277523006404843}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.304018, \"EndTime\": 1665673037.3040402, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 5}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9736388610289978, \"count\": 1, \"min\": 0.9736388610289978, \"max\": 0.9736388610289978}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3042216, \"EndTime\": 1665673037.304245, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 6}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8720021978154913, \"count\": 1, \"min\": 0.8720021978154913, \"max\": 0.8720021978154913}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3047087, \"EndTime\": 1665673037.304856, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 7}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0315409479914486, \"count\": 1, \"min\": 1.0315409479914486, \"max\": 1.0315409479914486}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.30494, \"EndTime\": 1665673037.3049626, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 8}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8065404806051168, \"count\": 1, \"min\": 0.8065404806051168, \"max\": 0.8065404806051168}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3050284, \"EndTime\": 1665673037.305047, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 9}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8620898272540118, \"count\": 1, \"min\": 0.8620898272540118, \"max\": 0.8620898272540118}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3051026, \"EndTime\": 1665673037.30512, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 10}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0346797908748593, \"count\": 1, \"min\": 1.0346797908748593, \"max\": 1.0346797908748593}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3051744, \"EndTime\": 1665673037.3051918, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"model\": 11}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9936064299162444, \"count\": 1, \"min\": 0.9936064299162444, \"max\": 0.9936064299162444}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=4, validation multiclass_cross_entropy_objective =1.0100545109929264\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=4, criteria=multiclass_cross_entropy_objective, value=0.8065404806051168\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saving model for epoch: 4\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saved checkpoint to \"/tmp/tmptta4f58y/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #progress_metric: host=algo-1, completed 33.333333333333336 % of epochs\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.2315865, \"EndTime\": 1665673037.3150609, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 4, \"Meta\": \"training_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 11656.0, \"count\": 1, \"min\": 11656, \"max\": 11656}, \"Total Batches Seen\": {\"sum\": 13.0, \"count\": 1, \"min\": 13, \"max\": 13}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 7.0, \"count\": 1, \"min\": 7, \"max\": 7}, \"Number of Records Since Last Reset\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Number of Batches Since Last Reset\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #throughput_metric: host=algo-1, train throughput=21239.646620057254 records/second\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.341] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 14, \"duration\": 25, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.34117, \"EndTime\": 1665673037.341229, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 0}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0152379760742187, \"count\": 1, \"min\": 1.0152379760742187, \"max\": 1.0152379760742187}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3413348, \"EndTime\": 1665673037.3413563, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 1}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0039544067382813, \"count\": 1, \"min\": 1.0039544067382813, \"max\": 1.0039544067382813}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3414288, \"EndTime\": 1665673037.3414476, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 2}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9525301513671875, \"count\": 1, \"min\": 0.9525301513671875, \"max\": 0.9525301513671875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3415062, \"EndTime\": 1665673037.3415258, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 3}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.959768310546875, \"count\": 1, \"min\": 0.959768310546875, \"max\": 0.959768310546875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3415856, \"EndTime\": 1665673037.341604, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 4}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0289783935546875, \"count\": 1, \"min\": 1.0289783935546875, \"max\": 1.0289783935546875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3416631, \"EndTime\": 1665673037.3416812, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 5}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9785779418945313, \"count\": 1, \"min\": 0.9785779418945313, \"max\": 0.9785779418945313}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.34175, \"EndTime\": 1665673037.34177, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 6}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8819891967773438, \"count\": 1, \"min\": 0.8819891967773438, \"max\": 0.8819891967773438}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3418286, \"EndTime\": 1665673037.3418455, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 7}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.035796875, \"count\": 1, \"min\": 1.035796875, \"max\": 1.035796875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3419025, \"EndTime\": 1665673037.3419206, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 8}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.816642578125, \"count\": 1, \"min\": 0.816642578125, \"max\": 0.816642578125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.341979, \"EndTime\": 1665673037.341998, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 9}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8850859985351562, \"count\": 1, \"min\": 0.8850859985351562, \"max\": 0.8850859985351562}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3420599, \"EndTime\": 1665673037.3420792, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 10}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0386148681640626, \"count\": 1, \"min\": 1.0386148681640626, \"max\": 1.0386148681640626}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3421388, \"EndTime\": 1665673037.3421566, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 11}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0105449829101563, \"count\": 1, \"min\": 1.0105449829101563, \"max\": 1.0105449829101563}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=5, train multiclass_cross_entropy_objective =1.0152379760742187\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.367] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 17, \"duration\": 11, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3717892, \"EndTime\": 1665673037.3718255, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 0}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9939004021721918, \"count\": 1, \"min\": 0.9939004021721918, \"max\": 0.9939004021721918}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3718908, \"EndTime\": 1665673037.3719044, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 1}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9781173843521256, \"count\": 1, \"min\": 0.9781173843521256, \"max\": 0.9781173843521256}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3719628, \"EndTime\": 1665673037.3719826, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 2}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9010299132750915, \"count\": 1, \"min\": 0.9010299132750915, \"max\": 0.9010299132750915}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3720448, \"EndTime\": 1665673037.372063, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 3}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9276772576409418, \"count\": 1, \"min\": 0.9276772576409418, \"max\": 0.9276772576409418}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.372121, \"EndTime\": 1665673037.3721397, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 4}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0094401728999507, \"count\": 1, \"min\": 1.0094401728999507, \"max\": 1.0094401728999507}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3721998, \"EndTime\": 1665673037.372219, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 5}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9608209283502253, \"count\": 1, \"min\": 0.9608209283502253, \"max\": 0.9608209283502253}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3722873, \"EndTime\": 1665673037.3723073, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 6}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8611121650214668, \"count\": 1, \"min\": 0.8611121650214668, \"max\": 0.8611121650214668}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3723664, \"EndTime\": 1665673037.3723843, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 7}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.018416877265449, \"count\": 1, \"min\": 1.018416877265449, \"max\": 1.018416877265449}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3724446, \"EndTime\": 1665673037.3724623, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 8}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.776808111517279, \"count\": 1, \"min\": 0.776808111517279, \"max\": 0.776808111517279}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.372521, \"EndTime\": 1665673037.372538, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 9}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0299277778144356, \"count\": 1, \"min\": 1.0299277778144356, \"max\": 1.0299277778144356}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3725975, \"EndTime\": 1665673037.3726163, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 10}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0237428819811023, \"count\": 1, \"min\": 1.0237428819811023, \"max\": 1.0237428819811023}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3726726, \"EndTime\": 1665673037.37269, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"model\": 11}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0481382490278364, \"count\": 1, \"min\": 1.0481382490278364, \"max\": 1.0481382490278364}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=5, validation multiclass_cross_entropy_objective =0.9939004021721918\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=5, criteria=multiclass_cross_entropy_objective, value=0.776808111517279\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Epoch 5: Loss improved. Updating best model\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saving model for epoch: 5\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saved checkpoint to \"/tmp/tmphu8y1zg8/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #progress_metric: host=algo-1, completed 40.0 % of epochs\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.3154159, \"EndTime\": 1665673037.3837898, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 5, \"Meta\": \"training_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 13432.0, \"count\": 1, \"min\": 13432, \"max\": 13432}, \"Total Batches Seen\": {\"sum\": 15.0, \"count\": 1, \"min\": 15, \"max\": 15}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 8.0, \"count\": 1, \"min\": 8, \"max\": 8}, \"Number of Records Since Last Reset\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Number of Batches Since Last Reset\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #throughput_metric: host=algo-1, train throughput=25916.527746272084 records/second\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.412] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 16, \"duration\": 27, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4121733, \"EndTime\": 1665673037.412227, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 0}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9983641967773438, \"count\": 1, \"min\": 0.9983641967773438, \"max\": 0.9983641967773438}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4122953, \"EndTime\": 1665673037.4123173, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 1}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9830233154296875, \"count\": 1, \"min\": 0.9830233154296875, \"max\": 0.9830233154296875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.412378, \"EndTime\": 1665673037.4123976, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 2}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.90822900390625, \"count\": 1, \"min\": 0.90822900390625, \"max\": 0.90822900390625}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4124517, \"EndTime\": 1665673037.4124699, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 3}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9347615966796875, \"count\": 1, \"min\": 0.9347615966796875, \"max\": 0.9347615966796875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4125233, \"EndTime\": 1665673037.4125402, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 4}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.01159619140625, \"count\": 1, \"min\": 1.01159619140625, \"max\": 1.01159619140625}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4125934, \"EndTime\": 1665673037.4126112, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 5}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9659964599609375, \"count\": 1, \"min\": 0.9659964599609375, \"max\": 0.9659964599609375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4126656, \"EndTime\": 1665673037.412683, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 6}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8716508178710938, \"count\": 1, \"min\": 0.8716508178710938, \"max\": 0.8716508178710938}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.412739, \"EndTime\": 1665673037.4127567, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 7}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.022560546875, \"count\": 1, \"min\": 1.022560546875, \"max\": 1.022560546875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4128003, \"EndTime\": 1665673037.412817, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 8}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.7877861938476562, \"count\": 1, \"min\": 0.7877861938476562, \"max\": 0.7877861938476562}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4128609, \"EndTime\": 1665673037.4128766, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 9}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.042639892578125, \"count\": 1, \"min\": 1.042639892578125, \"max\": 1.042639892578125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4129345, \"EndTime\": 1665673037.4129524, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 10}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0279864501953124, \"count\": 1, \"min\": 1.0279864501953124, \"max\": 1.0279864501953124}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4130068, \"EndTime\": 1665673037.4130235, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 11}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.056670166015625, \"count\": 1, \"min\": 1.056670166015625, \"max\": 1.056670166015625}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=6, train multiclass_cross_entropy_objective =0.9983641967773438\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.431] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 20, \"duration\": 9, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.434259, \"EndTime\": 1665673037.4342911, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 0}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9816924086562148, \"count\": 1, \"min\": 0.9816924086562148, \"max\": 0.9816924086562148}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4343562, \"EndTime\": 1665673037.4343774, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 1}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9640626649598818, \"count\": 1, \"min\": 0.9640626649598818, \"max\": 0.9640626649598818}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4344392, \"EndTime\": 1665673037.4344575, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 2}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8840011734146256, \"count\": 1, \"min\": 0.8840011734146256, \"max\": 0.8840011734146256}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4345086, \"EndTime\": 1665673037.4345267, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 3}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.913693058598149, \"count\": 1, \"min\": 0.913693058598149, \"max\": 0.913693058598149}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4345808, \"EndTime\": 1665673037.434598, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 4}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9919377919789907, \"count\": 1, \"min\": 0.9919377919789907, \"max\": 0.9919377919789907}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4346526, \"EndTime\": 1665673037.4346697, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 5}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9490948238888303, \"count\": 1, \"min\": 0.9490948238888303, \"max\": 0.9490948238888303}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4347255, \"EndTime\": 1665673037.434743, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 6}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8521690024985923, \"count\": 1, \"min\": 0.8521690024985923, \"max\": 0.8521690024985923}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4347892, \"EndTime\": 1665673037.4348044, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 7}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.007544096525725, \"count\": 1, \"min\": 1.007544096525725, \"max\": 1.007544096525725}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4348562, \"EndTime\": 1665673037.4348726, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 8}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7531444790127041, \"count\": 1, \"min\": 0.7531444790127041, \"max\": 0.7531444790127041}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4349246, \"EndTime\": 1665673037.4349403, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 9}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9661099545590512, \"count\": 1, \"min\": 0.9661099545590512, \"max\": 0.9661099545590512}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4349914, \"EndTime\": 1665673037.4350078, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 10}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0140147166209177, \"count\": 1, \"min\": 1.0140147166209177, \"max\": 1.0140147166209177}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4350655, \"EndTime\": 1665673037.4350827, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"model\": 11}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7726690618841497, \"count\": 1, \"min\": 0.7726690618841497, \"max\": 0.7726690618841497}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=6, validation multiclass_cross_entropy_objective =0.9816924086562148\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=6, criteria=multiclass_cross_entropy_objective, value=0.7531444790127041\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Epoch 6: Loss improved. Updating best model\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saving model for epoch: 6\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saved checkpoint to \"/tmp/tmproj72u4x/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #progress_metric: host=algo-1, completed 46.666666666666664 % of epochs\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.384144, \"EndTime\": 1665673037.446854, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 6, \"Meta\": \"training_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 15208.0, \"count\": 1, \"min\": 15208, \"max\": 15208}, \"Total Batches Seen\": {\"sum\": 17.0, \"count\": 1, \"min\": 17, \"max\": 17}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 9.0, \"count\": 1, \"min\": 9, \"max\": 9}, \"Number of Records Since Last Reset\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Number of Batches Since Last Reset\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #throughput_metric: host=algo-1, train throughput=28226.491087668244 records/second\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.475] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 18, \"duration\": 28, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4758885, \"EndTime\": 1665673037.475942, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 0}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9853231811523437, \"count\": 1, \"min\": 0.9853231811523437, \"max\": 0.9853231811523437}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4760225, \"EndTime\": 1665673037.476044, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 1}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9681892700195313, \"count\": 1, \"min\": 0.9681892700195313, \"max\": 0.9681892700195313}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4761066, \"EndTime\": 1665673037.476126, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 2}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.890293212890625, \"count\": 1, \"min\": 0.890293212890625, \"max\": 0.890293212890625}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4761846, \"EndTime\": 1665673037.476202, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 3}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9197091064453125, \"count\": 1, \"min\": 0.9197091064453125, \"max\": 0.9197091064453125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4762604, \"EndTime\": 1665673037.476278, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 4}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9950196533203125, \"count\": 1, \"min\": 0.9950196533203125, \"max\": 0.9950196533203125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4763331, \"EndTime\": 1665673037.47635, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 5}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9546382446289062, \"count\": 1, \"min\": 0.9546382446289062, \"max\": 0.9546382446289062}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.476403, \"EndTime\": 1665673037.4764204, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 6}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8637085571289063, \"count\": 1, \"min\": 0.8637085571289063, \"max\": 0.8637085571289063}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4764767, \"EndTime\": 1665673037.476495, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 7}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0112341918945313, \"count\": 1, \"min\": 1.0112341918945313, \"max\": 1.0112341918945313}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4765494, \"EndTime\": 1665673037.476565, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 8}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.764803955078125, \"count\": 1, \"min\": 0.764803955078125, \"max\": 0.764803955078125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4766185, \"EndTime\": 1665673037.4766352, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 9}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0003087158203126, \"count\": 1, \"min\": 1.0003087158203126, \"max\": 1.0003087158203126}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.476686, \"EndTime\": 1665673037.4767017, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 10}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0180759887695312, \"count\": 1, \"min\": 1.0180759887695312, \"max\": 1.0180759887695312}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4767516, \"EndTime\": 1665673037.476767, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 11}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.7881486206054688, \"count\": 1, \"min\": 0.7881486206054688, \"max\": 0.7881486206054688}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=7, train multiclass_cross_entropy_objective =0.9853231811523437\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.498] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 23, \"duration\": 11, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5025156, \"EndTime\": 1665673037.5025492, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 0}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9710025959186726, \"count\": 1, \"min\": 0.9710025959186726, \"max\": 0.9710025959186726}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5026374, \"EndTime\": 1665673037.5026598, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 1}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9522011559288781, \"count\": 1, \"min\": 0.9522011559288781, \"max\": 0.9522011559288781}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.502723, \"EndTime\": 1665673037.50274, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 2}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8751449584960938, \"count\": 1, \"min\": 0.8751449584960938, \"max\": 0.8751449584960938}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5027938, \"EndTime\": 1665673037.5028121, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 3}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9035690582550324, \"count\": 1, \"min\": 0.9035690582550324, \"max\": 0.9035690582550324}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5028667, \"EndTime\": 1665673037.5028784, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 4}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9752499692074887, \"count\": 1, \"min\": 0.9752499692074887, \"max\": 0.9752499692074887}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5029254, \"EndTime\": 1665673037.5029423, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 5}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9385290747290259, \"count\": 1, \"min\": 0.9385290747290259, \"max\": 0.9385290747290259}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5029948, \"EndTime\": 1665673037.5030115, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 6}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8457017503343187, \"count\": 1, \"min\": 0.8457017503343187, \"max\": 0.8457017503343187}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.503061, \"EndTime\": 1665673037.503078, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 7}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9978819151182432, \"count\": 1, \"min\": 0.9978819151182432, \"max\": 0.9978819151182432}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5031295, \"EndTime\": 1665673037.503146, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 8}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7345062805725647, \"count\": 1, \"min\": 0.7345062805725647, \"max\": 0.7345062805725647}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5032167, \"EndTime\": 1665673037.5032356, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 9}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8614959029464034, \"count\": 1, \"min\": 0.8614959029464034, \"max\": 0.8614959029464034}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5032833, \"EndTime\": 1665673037.5032938, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 10}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.0053842905405406, \"count\": 1, \"min\": 1.0053842905405406, \"max\": 1.0053842905405406}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5033417, \"EndTime\": 1665673037.5033584, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"model\": 11}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7539334683804899, \"count\": 1, \"min\": 0.7539334683804899, \"max\": 0.7539334683804899}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=7, validation multiclass_cross_entropy_objective =0.9710025959186726\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=7, criteria=multiclass_cross_entropy_objective, value=0.7345062805725647\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Epoch 7: Loss improved. Updating best model\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saving model for epoch: 7\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saved checkpoint to \"/tmp/tmp0penalxn/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #progress_metric: host=algo-1, completed 53.333333333333336 % of epochs\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.4472294, \"EndTime\": 1665673037.513333, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 7, \"Meta\": \"training_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 16984.0, \"count\": 1, \"min\": 16984, \"max\": 16984}, \"Total Batches Seen\": {\"sum\": 19.0, \"count\": 1, \"min\": 19, \"max\": 19}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 10.0, \"count\": 1, \"min\": 10, \"max\": 10}, \"Number of Records Since Last Reset\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Number of Batches Since Last Reset\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #throughput_metric: host=algo-1, train throughput=26802.11098517967 records/second\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.536] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 20, \"duration\": 22, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5364099, \"EndTime\": 1665673037.536466, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 0}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9742128295898438, \"count\": 1, \"min\": 0.9742128295898438, \"max\": 0.9742128295898438}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5365443, \"EndTime\": 1665673037.536565, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 1}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9560975952148437, \"count\": 1, \"min\": 0.9560975952148437, \"max\": 0.9560975952148437}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.536629, \"EndTime\": 1665673037.5366483, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 2}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.88151708984375, \"count\": 1, \"min\": 0.88151708984375, \"max\": 0.88151708984375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.536707, \"EndTime\": 1665673037.5367255, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 3}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9090670166015625, \"count\": 1, \"min\": 0.9090670166015625, \"max\": 0.9090670166015625}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5367928, \"EndTime\": 1665673037.5368114, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 4}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.979219482421875, \"count\": 1, \"min\": 0.979219482421875, \"max\": 0.979219482421875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5368686, \"EndTime\": 1665673037.536885, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 5}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9442431030273437, \"count\": 1, \"min\": 0.9442431030273437, \"max\": 0.9442431030273437}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.53694, \"EndTime\": 1665673037.5369568, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 6}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.857370361328125, \"count\": 1, \"min\": 0.857370361328125, \"max\": 0.857370361328125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5370102, \"EndTime\": 1665673037.5370266, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 7}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0012473754882814, \"count\": 1, \"min\": 1.0012473754882814, \"max\": 1.0012473754882814}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5370896, \"EndTime\": 1665673037.5371606, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 8}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.7468468017578125, \"count\": 1, \"min\": 0.7468468017578125, \"max\": 0.7468468017578125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5372255, \"EndTime\": 1665673037.537244, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 9}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8839507446289062, \"count\": 1, \"min\": 0.8839507446289062, \"max\": 0.8839507446289062}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5372958, \"EndTime\": 1665673037.5373116, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 10}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.009175048828125, \"count\": 1, \"min\": 1.009175048828125, \"max\": 1.009175048828125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5373425, \"EndTime\": 1665673037.537351, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 11}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.7669869384765625, \"count\": 1, \"min\": 0.7669869384765625, \"max\": 0.7669869384765625}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=8, train multiclass_cross_entropy_objective =0.9742128295898438\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.563] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 26, \"duration\": 15, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5666645, \"EndTime\": 1665673037.5666983, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 0}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9585014549461571, \"count\": 1, \"min\": 0.9585014549461571, \"max\": 0.9585014549461571}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5667663, \"EndTime\": 1665673037.566788, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 1}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9375753316793356, \"count\": 1, \"min\": 0.9375753316793356, \"max\": 0.9375753316793356}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5668511, \"EndTime\": 1665673037.5668707, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 2}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8565547358882319, \"count\": 1, \"min\": 0.8565547358882319, \"max\": 0.8565547358882319}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.56694, \"EndTime\": 1665673037.5669599, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 3}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8892968667520059, \"count\": 1, \"min\": 0.8892968667520059, \"max\": 0.8892968667520059}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5670147, \"EndTime\": 1665673037.5670319, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 4}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9593923757742117, \"count\": 1, \"min\": 0.9593923757742117, \"max\": 0.9593923757742117}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5670652, \"EndTime\": 1665673037.5670748, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 5}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9286073564409135, \"count\": 1, \"min\": 0.9286073564409135, \"max\": 0.9286073564409135}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5671012, \"EndTime\": 1665673037.5671103, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 6}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.839864782384924, \"count\": 1, \"min\": 0.839864782384924, \"max\": 0.839864782384924}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5671604, \"EndTime\": 1665673037.5671763, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 7}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9874037321623381, \"count\": 1, \"min\": 0.9874037321623381, \"max\": 0.9874037321623381}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5672526, \"EndTime\": 1665673037.5672693, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 8}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7201382748715512, \"count\": 1, \"min\": 0.7201382748715512, \"max\": 0.7201382748715512}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5685706, \"EndTime\": 1665673037.5685987, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 9}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7733155671540681, \"count\": 1, \"min\": 0.7733155671540681, \"max\": 0.7733155671540681}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5686681, \"EndTime\": 1665673037.5686882, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 10}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9966917295713682, \"count\": 1, \"min\": 0.9966917295713682, \"max\": 0.9966917295713682}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5687594, \"EndTime\": 1665673037.56878, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"model\": 11}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7390858418232685, \"count\": 1, \"min\": 0.7390858418232685, \"max\": 0.7390858418232685}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=8, validation multiclass_cross_entropy_objective =0.9585014549461571\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=8, criteria=multiclass_cross_entropy_objective, value=0.7201382748715512\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Epoch 8: Loss improved. Updating best model\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saving model for epoch: 8\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saved checkpoint to \"/tmp/tmponermtw6/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #progress_metric: host=algo-1, completed 60.0 % of epochs\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5136378, \"EndTime\": 1665673037.577426, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 8, \"Meta\": \"training_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 18760.0, \"count\": 1, \"min\": 18760, \"max\": 18760}, \"Total Batches Seen\": {\"sum\": 21.0, \"count\": 1, \"min\": 21, \"max\": 21}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 11.0, \"count\": 1, \"min\": 11, \"max\": 11}, \"Number of Records Since Last Reset\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Number of Batches Since Last Reset\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #throughput_metric: host=algo-1, train throughput=27773.119413001656 records/second\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.598] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 22, \"duration\": 20, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5987446, \"EndTime\": 1665673037.5987914, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 0}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9618958129882812, \"count\": 1, \"min\": 0.9618958129882812, \"max\": 0.9618958129882812}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5988739, \"EndTime\": 1665673037.598897, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 1}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.941915771484375, \"count\": 1, \"min\": 0.941915771484375, \"max\": 0.941915771484375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5989392, \"EndTime\": 1665673037.5989497, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 2}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8639841918945312, \"count\": 1, \"min\": 0.8639841918945312, \"max\": 0.8639841918945312}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5989969, \"EndTime\": 1665673037.5990155, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 3}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8950126953125, \"count\": 1, \"min\": 0.8950126953125, \"max\": 0.8950126953125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5990717, \"EndTime\": 1665673037.5990891, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 4}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.964184814453125, \"count\": 1, \"min\": 0.964184814453125, \"max\": 0.964184814453125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.599147, \"EndTime\": 1665673037.5991654, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 5}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9346255493164063, \"count\": 1, \"min\": 0.9346255493164063, \"max\": 0.9346255493164063}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5992477, \"EndTime\": 1665673037.5992665, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 6}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8526281127929688, \"count\": 1, \"min\": 0.8526281127929688, \"max\": 0.8526281127929688}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5993226, \"EndTime\": 1665673037.599341, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 7}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.990891357421875, \"count\": 1, \"min\": 0.990891357421875, \"max\": 0.990891357421875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5993958, \"EndTime\": 1665673037.5994127, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 8}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.733297607421875, \"count\": 1, \"min\": 0.733297607421875, \"max\": 0.733297607421875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.599479, \"EndTime\": 1665673037.5994995, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 9}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8032108764648438, \"count\": 1, \"min\": 0.8032108764648438, \"max\": 0.8032108764648438}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5995593, \"EndTime\": 1665673037.5995781, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 10}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.0005331420898438, \"count\": 1, \"min\": 1.0005331420898438, \"max\": 1.0005331420898438}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5996337, \"EndTime\": 1665673037.5996516, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 11}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.755513671875, \"count\": 1, \"min\": 0.755513671875, \"max\": 0.755513671875}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=9, train multiclass_cross_entropy_objective =0.9618958129882812\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.623] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 29, \"duration\": 11, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6280344, \"EndTime\": 1665673037.6280684, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 0}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9445367761560388, \"count\": 1, \"min\": 0.9445367761560388, \"max\": 0.9445367761560388}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6281362, \"EndTime\": 1665673037.6281567, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 1}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9207396636138091, \"count\": 1, \"min\": 0.9207396636138091, \"max\": 0.9207396636138091}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6282222, \"EndTime\": 1665673037.628242, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 2}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8297453184385557, \"count\": 1, \"min\": 0.8297453184385557, \"max\": 0.8297453184385557}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6283047, \"EndTime\": 1665673037.6283233, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 3}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8711527231577281, \"count\": 1, \"min\": 0.8711527231577281, \"max\": 0.8711527231577281}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6283832, \"EndTime\": 1665673037.6284018, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 4}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9443805454013584, \"count\": 1, \"min\": 0.9443805454013584, \"max\": 0.9443805454013584}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6284602, \"EndTime\": 1665673037.6284792, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 5}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.919510368828301, \"count\": 1, \"min\": 0.919510368828301, \"max\": 0.919510368828301}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6285365, \"EndTime\": 1665673037.6285546, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 6}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8361467241166948, \"count\": 1, \"min\": 0.8361467241166948, \"max\": 0.8361467241166948}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.628611, \"EndTime\": 1665673037.6286297, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 7}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9760390273085585, \"count\": 1, \"min\": 0.9760390273085585, \"max\": 0.9760390273085585}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6286874, \"EndTime\": 1665673037.6287055, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 8}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7090885746586431, \"count\": 1, \"min\": 0.7090885746586431, \"max\": 0.7090885746586431}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6287632, \"EndTime\": 1665673037.6287808, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 9}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8904751614407376, \"count\": 1, \"min\": 0.8904751614407376, \"max\": 0.8904751614407376}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6288366, \"EndTime\": 1665673037.6288552, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 10}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9873264072177647, \"count\": 1, \"min\": 0.9873264072177647, \"max\": 0.9873264072177647}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6289139, \"EndTime\": 1665673037.6289327, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"model\": 11}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.732469232232721, \"count\": 1, \"min\": 0.732469232232721, \"max\": 0.732469232232721}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=9, validation multiclass_cross_entropy_objective =0.9445367761560388\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=9, criteria=multiclass_cross_entropy_objective, value=0.7090885746586431\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Epoch 9: Loss improved. Updating best model\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saving model for epoch: 9\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saved checkpoint to \"/tmp/tmpz36swfzg/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #progress_metric: host=algo-1, completed 66.66666666666667 % of epochs\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.5777638, \"EndTime\": 1665673037.6370306, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 9, \"Meta\": \"training_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 20536.0, \"count\": 1, \"min\": 20536, \"max\": 20536}, \"Total Batches Seen\": {\"sum\": 23.0, \"count\": 1, \"min\": 23, \"max\": 23}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 12.0, \"count\": 1, \"min\": 12, \"max\": 12}, \"Number of Records Since Last Reset\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Number of Batches Since Last Reset\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #throughput_metric: host=algo-1, train throughput=29887.912178916198 records/second\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.663] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 24, \"duration\": 25, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6635077, \"EndTime\": 1665673037.6636925, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 0}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9485713500976563, \"count\": 1, \"min\": 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\"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 3}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8776348876953125, \"count\": 1, \"min\": 0.8776348876953125, \"max\": 0.8776348876953125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6640153, \"EndTime\": 1665673037.6640346, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 4}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.949911376953125, \"count\": 1, \"min\": 0.949911376953125, \"max\": 0.949911376953125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.66409, \"EndTime\": 1665673037.6641073, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 5}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9256568603515625, \"count\": 1, \"min\": 0.9256568603515625, \"max\": 0.9256568603515625}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6641643, \"EndTime\": 1665673037.6641817, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 6}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8485236206054687, \"count\": 1, \"min\": 0.8485236206054687, \"max\": 0.8485236206054687}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6642387, \"EndTime\": 1665673037.6642568, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 7}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9800468139648437, \"count\": 1, \"min\": 0.9800468139648437, \"max\": 0.9800468139648437}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6643126, \"EndTime\": 1665673037.6643298, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 8}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.7232676391601562, \"count\": 1, \"min\": 0.7232676391601562, \"max\": 0.7232676391601562}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.664385, \"EndTime\": 1665673037.6644032, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 9}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9164950561523437, \"count\": 1, \"min\": 0.9164950561523437, \"max\": 0.9164950561523437}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.664458, \"EndTime\": 1665673037.6644757, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 10}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9916439819335937, \"count\": 1, \"min\": 0.9916439819335937, \"max\": 0.9916439819335937}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6645317, \"EndTime\": 1665673037.6645486, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 11}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.747091552734375, \"count\": 1, \"min\": 0.747091552734375, \"max\": 0.747091552734375}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=10, train multiclass_cross_entropy_objective =0.9485713500976563\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.685] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 32, \"duration\": 11, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6891482, \"EndTime\": 1665673037.689182, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 0}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9316181492161106, \"count\": 1, \"min\": 0.9316181492161106, \"max\": 0.9316181492161106}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6892478, \"EndTime\": 1665673037.6892693, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 1}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9051046285543356, \"count\": 1, \"min\": 0.9051046285543356, \"max\": 0.9051046285543356}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.689333, \"EndTime\": 1665673037.6893525, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 2}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8061451267551731, \"count\": 1, \"min\": 0.8061451267551731, \"max\": 0.8061451267551731}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6894138, \"EndTime\": 1665673037.6894333, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 3}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8541580062728744, \"count\": 1, \"min\": 0.8541580062728744, \"max\": 0.8541580062728744}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6894913, \"EndTime\": 1665673037.6895096, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 4}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9302162651543144, \"count\": 1, \"min\": 0.9302162651543144, \"max\": 0.9302162651543144}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.689569, \"EndTime\": 1665673037.689587, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 5}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9107974628070453, \"count\": 1, \"min\": 0.9107974628070453, \"max\": 0.9107974628070453}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.689629, \"EndTime\": 1665673037.6896453, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 6}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8320942784214879, \"count\": 1, \"min\": 0.8320942784214879, \"max\": 0.8320942784214879}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6896908, \"EndTime\": 1665673037.6897075, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 7}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.965047887853674, \"count\": 1, \"min\": 0.965047887853674, \"max\": 0.965047887853674}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6897604, \"EndTime\": 1665673037.6897802, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 8}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.700357385583826, \"count\": 1, \"min\": 0.700357385583826, \"max\": 0.700357385583826}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6898456, \"EndTime\": 1665673037.68986, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 9}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 1.1265192117776957, \"count\": 1, \"min\": 1.1265192117776957, \"max\": 1.1265192117776957}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6899111, \"EndTime\": 1665673037.6899285, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 10}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9778387396185247, \"count\": 1, \"min\": 0.9778387396185247, \"max\": 0.9778387396185247}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6899807, \"EndTime\": 1665673037.6899962, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"model\": 11}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7242622719154702, \"count\": 1, \"min\": 0.7242622719154702, \"max\": 0.7242622719154702}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=10, validation multiclass_cross_entropy_objective =0.9316181492161106\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=10, criteria=multiclass_cross_entropy_objective, value=0.700357385583826\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Epoch 10: Loss improved. Updating best model\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saving model for epoch: 10\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saved checkpoint to \"/tmp/tmp7tjf6lpm/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #progress_metric: host=algo-1, completed 73.33333333333333 % of epochs\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.6373594, \"EndTime\": 1665673037.7019987, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 10, \"Meta\": \"training_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 22312.0, \"count\": 1, \"min\": 22312, \"max\": 22312}, \"Total Batches Seen\": {\"sum\": 25.0, \"count\": 1, \"min\": 25, \"max\": 25}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 13.0, \"count\": 1, \"min\": 13, \"max\": 13}, \"Number of Records Since Last Reset\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Number of Batches Since Last Reset\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #throughput_metric: host=algo-1, train throughput=27416.37494019183 records/second\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.726] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 26, \"duration\": 24, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7266119, \"EndTime\": 1665673037.726666, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 0}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.936486328125, \"count\": 1, \"min\": 0.936486328125, \"max\": 0.936486328125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7268438, \"EndTime\": 1665673037.7268705, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 1}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9114187622070312, \"count\": 1, \"min\": 0.9114187622070312, \"max\": 0.9114187622070312}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7270062, \"EndTime\": 1665673037.727033, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 2}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8171005859375, \"count\": 1, \"min\": 0.8171005859375, \"max\": 0.8171005859375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7271023, \"EndTime\": 1665673037.7271204, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 3}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8616476440429688, \"count\": 1, \"min\": 0.8616476440429688, \"max\": 0.8616476440429688}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7271771, \"EndTime\": 1665673037.7272735, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 4}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9363878784179688, \"count\": 1, \"min\": 0.9363878784179688, \"max\": 0.9363878784179688}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7273402, \"EndTime\": 1665673037.7273605, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 5}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9172357177734375, \"count\": 1, \"min\": 0.9172357177734375, \"max\": 0.9172357177734375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7274191, \"EndTime\": 1665673037.7274394, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 6}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8457938842773437, \"count\": 1, \"min\": 0.8457938842773437, \"max\": 0.8457938842773437}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7274945, \"EndTime\": 1665673037.727513, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 7}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9697664184570313, \"count\": 1, \"min\": 0.9697664184570313, \"max\": 0.9697664184570313}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7275677, \"EndTime\": 1665673037.7275846, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 8}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.7157525024414062, \"count\": 1, \"min\": 0.7157525024414062, \"max\": 0.7157525024414062}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7276373, \"EndTime\": 1665673037.727655, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 9}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 1.1543360595703125, \"count\": 1, \"min\": 1.1543360595703125, \"max\": 1.1543360595703125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7277076, \"EndTime\": 1665673037.7277248, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 10}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.982904296875, \"count\": 1, \"min\": 0.982904296875, \"max\": 0.982904296875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7277777, \"EndTime\": 1665673037.7277956, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 11}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.7418512573242187, \"count\": 1, \"min\": 0.7418512573242187, \"max\": 0.7418512573242187}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=11, train multiclass_cross_entropy_objective =0.936486328125\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.752] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 35, \"duration\": 12, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.755824, \"EndTime\": 1665673037.7558572, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 0}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9206571149396466, \"count\": 1, \"min\": 0.9206571149396466, \"max\": 0.9206571149396466}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.755925, \"EndTime\": 1665673037.7559385, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 1}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8926412221547719, \"count\": 1, \"min\": 0.8926412221547719, \"max\": 0.8926412221547719}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7560031, \"EndTime\": 1665673037.7560208, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 2}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.79347174017279, \"count\": 1, \"min\": 0.79347174017279, \"max\": 0.79347174017279}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.756076, \"EndTime\": 1665673037.756092, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 3}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8417616148252745, \"count\": 1, \"min\": 0.8417616148252745, \"max\": 0.8417616148252745}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.756147, \"EndTime\": 1665673037.756165, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 4}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9168795336474169, \"count\": 1, \"min\": 0.9168795336474169, \"max\": 0.9168795336474169}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7562199, \"EndTime\": 1665673037.7562377, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 5}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9027696214280687, \"count\": 1, \"min\": 0.9027696214280687, \"max\": 0.9027696214280687}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7562907, \"EndTime\": 1665673037.756308, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 6}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8300546182168497, \"count\": 1, \"min\": 0.8300546182168497, \"max\": 0.8300546182168497}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.756356, \"EndTime\": 1665673037.7563736, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 7}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9552351118208052, \"count\": 1, \"min\": 0.9552351118208052, \"max\": 0.9552351118208052}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.756428, \"EndTime\": 1665673037.7564447, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 8}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.6932918101817638, \"count\": 1, \"min\": 0.6932918101817638, \"max\": 0.6932918101817638}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7564921, \"EndTime\": 1665673037.7565084, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 9}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8486811319986979, \"count\": 1, \"min\": 0.8486811319986979, \"max\": 0.8486811319986979}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.7565515, \"EndTime\": 1665673037.7565672, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 10}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9689559936523438, \"count\": 1, \"min\": 0.9689559936523438, \"max\": 0.9689559936523438}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.756625, \"EndTime\": 1665673037.7566423, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"model\": 11}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7209465095588753, \"count\": 1, \"min\": 0.7209465095588753, \"max\": 0.7209465095588753}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=11, validation multiclass_cross_entropy_objective =0.9206571149396466\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=11, criteria=multiclass_cross_entropy_objective, value=0.6932918101817638\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Epoch 11: Loss improved. Updating best model\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saving model for epoch: 11\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saved checkpoint to \"/tmp/tmp6hc8zaup/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #progress_metric: host=algo-1, completed 80.0 % of epochs\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.702322, \"EndTime\": 1665673037.769083, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 11, \"Meta\": \"training_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 24088.0, \"count\": 1, \"min\": 24088, \"max\": 24088}, \"Total Batches Seen\": {\"sum\": 27.0, \"count\": 1, \"min\": 27, \"max\": 27}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 14.0, \"count\": 1, \"min\": 14, \"max\": 14}, \"Number of Records Since Last Reset\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Number of Batches Since Last Reset\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #throughput_metric: host=algo-1, train throughput=26511.082297672434 records/second\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.803] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 28, \"duration\": 33, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8037777, \"EndTime\": 1665673037.8038354, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 0}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9263245849609375, \"count\": 1, \"min\": 0.9263245849609375, \"max\": 0.9263245849609375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.804003, \"EndTime\": 1665673037.8040307, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 1}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8999277954101562, \"count\": 1, \"min\": 0.8999277954101562, \"max\": 0.8999277954101562}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8041453, \"EndTime\": 1665673037.8041902, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 2}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8059401245117187, \"count\": 1, \"min\": 0.8059401245117187, \"max\": 0.8059401245117187}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8043056, \"EndTime\": 1665673037.804326, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 3}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8501904296875, \"count\": 1, \"min\": 0.8501904296875, \"max\": 0.8501904296875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8044584, \"EndTime\": 1665673037.8044808, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 4}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9235873413085938, \"count\": 1, \"min\": 0.9235873413085938, \"max\": 0.9235873413085938}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8046262, \"EndTime\": 1665673037.8046494, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 5}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9092908325195312, \"count\": 1, \"min\": 0.9092908325195312, \"max\": 0.9092908325195312}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.804715, \"EndTime\": 1665673037.804734, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 6}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8428941040039063, \"count\": 1, \"min\": 0.8428941040039063, \"max\": 0.8428941040039063}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8047967, \"EndTime\": 1665673037.804818, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 7}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9606159057617187, \"count\": 1, \"min\": 0.9606159057617187, \"max\": 0.9606159057617187}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8048704, \"EndTime\": 1665673037.8048904, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 8}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.7100371704101562, \"count\": 1, \"min\": 0.7100371704101562, \"max\": 0.7100371704101562}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8049428, \"EndTime\": 1665673037.80496, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 9}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8775864868164063, \"count\": 1, \"min\": 0.8775864868164063, \"max\": 0.8775864868164063}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8050134, \"EndTime\": 1665673037.8050344, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 10}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9748095703125, \"count\": 1, \"min\": 0.9748095703125, \"max\": 0.9748095703125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8051345, \"EndTime\": 1665673037.8051581, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 11}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.7370922241210938, \"count\": 1, \"min\": 0.7370922241210938, \"max\": 0.7370922241210938}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=12, train multiclass_cross_entropy_objective =0.9263245849609375\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.834] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 38, \"duration\": 17, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8390992, \"EndTime\": 1665673037.839154, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 0}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9108252310538077, \"count\": 1, \"min\": 0.9108252310538077, \"max\": 0.9108252310538077}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.839286, \"EndTime\": 1665673037.83931, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 1}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8820520349451013, \"count\": 1, \"min\": 0.8820520349451013, \"max\": 0.8820520349451013}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8393764, \"EndTime\": 1665673037.839396, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 2}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7874741425385346, \"count\": 1, \"min\": 0.7874741425385346, \"max\": 0.7874741425385346}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8394566, \"EndTime\": 1665673037.8394766, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 3}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8325396701022312, \"count\": 1, \"min\": 0.8325396701022312, \"max\": 0.8325396701022312}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8395512, \"EndTime\": 1665673037.8395696, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 4}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.904331585308453, \"count\": 1, \"min\": 0.904331585308453, \"max\": 0.904331585308453}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8396287, \"EndTime\": 1665673037.8396475, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 5}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8949262601835234, \"count\": 1, \"min\": 0.8949262601835234, \"max\": 0.8949262601835234}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8397145, \"EndTime\": 1665673037.8397372, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 6}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8271030047992328, \"count\": 1, \"min\": 0.8271030047992328, \"max\": 0.8271030047992328}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8398128, \"EndTime\": 1665673037.8398314, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 7}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9462568953230575, \"count\": 1, \"min\": 0.9462568953230575, \"max\": 0.9462568953230575}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8399074, \"EndTime\": 1665673037.8399296, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 8}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.6876294935071791, \"count\": 1, \"min\": 0.6876294935071791, \"max\": 0.6876294935071791}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8399894, \"EndTime\": 1665673037.840008, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 9}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9615854486688837, \"count\": 1, \"min\": 0.9615854486688837, \"max\": 0.9615854486688837}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8400567, \"EndTime\": 1665673037.840073, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 10}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9608302760768581, \"count\": 1, \"min\": 0.9608302760768581, \"max\": 0.9608302760768581}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.840123, \"EndTime\": 1665673037.840138, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"model\": 11}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.715646692224451, \"count\": 1, \"min\": 0.715646692224451, \"max\": 0.715646692224451}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=12, validation multiclass_cross_entropy_objective =0.9108252310538077\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=12, criteria=multiclass_cross_entropy_objective, value=0.6876294935071791\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Epoch 12: Loss improved. Updating best model\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saving model for epoch: 12\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Saved checkpoint to \"/tmp/tmpjdowewv8/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #progress_metric: host=algo-1, completed 86.66666666666667 % of epochs\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.76956, \"EndTime\": 1665673037.851556, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 12, \"Meta\": \"training_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 25864.0, \"count\": 1, \"min\": 25864, \"max\": 25864}, \"Total Batches Seen\": {\"sum\": 29.0, \"count\": 1, \"min\": 29, \"max\": 29}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 15.0, \"count\": 1, \"min\": 15, \"max\": 15}, \"Number of Records Since Last Reset\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Number of Batches Since Last Reset\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #throughput_metric: host=algo-1, train throughput=21611.78118644412 records/second\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.887] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 30, \"duration\": 35, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8879917, \"EndTime\": 1665673037.8880556, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 0}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9170615234375, \"count\": 1, \"min\": 0.9170615234375, \"max\": 0.9170615234375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8884385, \"EndTime\": 1665673037.8885007, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 1}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.890017822265625, \"count\": 1, \"min\": 0.890017822265625, \"max\": 0.890017822265625}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8888245, \"EndTime\": 1665673037.8888555, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 2}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8010418090820313, \"count\": 1, \"min\": 0.8010418090820313, \"max\": 0.8010418090820313}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.888983, \"EndTime\": 1665673037.889006, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 3}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8416005249023437, \"count\": 1, \"min\": 0.8416005249023437, \"max\": 0.8416005249023437}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8890705, \"EndTime\": 1665673037.8890886, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 4}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.911470703125, \"count\": 1, \"min\": 0.911470703125, \"max\": 0.911470703125}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.889145, \"EndTime\": 1665673037.889162, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 5}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.901758544921875, \"count\": 1, \"min\": 0.901758544921875, \"max\": 0.901758544921875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.889218, \"EndTime\": 1665673037.8892348, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 6}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8414108276367187, \"count\": 1, \"min\": 0.8414108276367187, \"max\": 0.8414108276367187}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.88929, \"EndTime\": 1665673037.889312, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 7}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9520338134765625, \"count\": 1, \"min\": 0.9520338134765625, \"max\": 0.9520338134765625}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.889369, \"EndTime\": 1665673037.8893833, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 8}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.7057743530273437, \"count\": 1, \"min\": 0.7057743530273437, \"max\": 0.7057743530273437}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8894389, \"EndTime\": 1665673037.8894577, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 9}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.994546630859375, \"count\": 1, \"min\": 0.994546630859375, \"max\": 0.994546630859375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.889517, \"EndTime\": 1665673037.889533, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 10}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9672753295898437, \"count\": 1, \"min\": 0.9672753295898437, \"max\": 0.9672753295898437}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8895938, \"EndTime\": 1665673037.8896081, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 11}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.7346845092773437, \"count\": 1, \"min\": 0.7346845092773437, \"max\": 0.7346845092773437}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=13, train multiclass_cross_entropy_objective =0.9170615234375\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:17.987] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 41, \"duration\": 47, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.9919965, \"EndTime\": 1665673037.9920576, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 0}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9007824734524563, \"count\": 1, \"min\": 0.9007824734524563, \"max\": 0.9007824734524563}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.9924047, \"EndTime\": 1665673037.992433, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 1}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8710235045836853, \"count\": 1, \"min\": 0.8710235045836853, \"max\": 0.8710235045836853}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.9927757, \"EndTime\": 1665673037.992841, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 2}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7801455935916385, \"count\": 1, \"min\": 0.7801455935916385, \"max\": 0.7801455935916385}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.993141, \"EndTime\": 1665673037.9931672, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 3}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8227114978137317, \"count\": 1, \"min\": 0.8227114978137317, \"max\": 0.8227114978137317}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.9934855, \"EndTime\": 1665673037.9935112, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 4}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8925252003712697, \"count\": 1, \"min\": 0.8925252003712697, \"max\": 0.8925252003712697}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.9938214, \"EndTime\": 1665673037.9938476, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 5}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8877381333359727, \"count\": 1, \"min\": 0.8877381333359727, \"max\": 0.8877381333359727}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.9941795, \"EndTime\": 1665673037.9942055, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 6}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8262692013302365, \"count\": 1, \"min\": 0.8262692013302365, \"max\": 0.8262692013302365}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.9947991, \"EndTime\": 1665673037.994826, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 7}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.937435734379399, \"count\": 1, \"min\": 0.937435734379399, \"max\": 0.937435734379399}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.9951158, \"EndTime\": 1665673037.995141, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 8}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.6832418355855856, \"count\": 1, \"min\": 0.6832418355855856, \"max\": 0.6832418355855856}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.9954727, \"EndTime\": 1665673037.9954982, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 9}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7841880042273719, \"count\": 1, \"min\": 0.7841880042273719, \"max\": 0.7841880042273719}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.995809, \"EndTime\": 1665673037.9958344, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 10}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9531310485289978, \"count\": 1, \"min\": 0.9531310485289978, \"max\": 0.9531310485289978}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.996152, \"EndTime\": 1665673037.9961774, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"model\": 11}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7147295840151675, \"count\": 1, \"min\": 0.7147295840151675, \"max\": 0.7147295840151675}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #quality_metric: host=algo-1, epoch=13, validation multiclass_cross_entropy_objective =0.9007824734524563\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=13, criteria=multiclass_cross_entropy_objective, value=0.6832418355855856\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:17 INFO 140479147329344] Epoch 13: Loss improved. Updating best model\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] Saving model for epoch: 13\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] Saved checkpoint to \"/tmp/tmp2wwg31by/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #progress_metric: host=algo-1, completed 93.33333333333333 % of epochs\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673037.8518918, \"EndTime\": 1665673038.0115635, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 13, \"Meta\": \"training_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 27640.0, \"count\": 1, \"min\": 27640, \"max\": 27640}, \"Total Batches Seen\": {\"sum\": 31.0, \"count\": 1, \"min\": 31, \"max\": 31}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 16.0, \"count\": 1, \"min\": 16, \"max\": 16}, \"Number of Records Since Last Reset\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Number of Batches Since Last Reset\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #throughput_metric: host=algo-1, train throughput=11092.919321476596 records/second\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:18.058] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/train\", \"epoch\": 32, \"duration\": 46, \"num_examples\": 2, \"num_bytes\": 92352}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.0590234, \"EndTime\": 1665673038.0590909, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 0}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9072907104492187, \"count\": 1, \"min\": 0.9072907104492187, \"max\": 0.9072907104492187}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.0595117, \"EndTime\": 1665673038.0595717, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 1}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8793280029296875, \"count\": 1, \"min\": 0.8793280029296875, \"max\": 0.8793280029296875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.0600963, \"EndTime\": 1665673038.060129, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 2}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.7944518432617188, \"count\": 1, \"min\": 0.7944518432617188, \"max\": 0.7944518432617188}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.0604727, \"EndTime\": 1665673038.0605423, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 3}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8320138549804688, \"count\": 1, \"min\": 0.8320138549804688, \"max\": 0.8320138549804688}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.0608864, \"EndTime\": 1665673038.0609136, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 4}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8999974975585937, \"count\": 1, \"min\": 0.8999974975585937, \"max\": 0.8999974975585937}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.0612574, \"EndTime\": 1665673038.0613744, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 5}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8945975341796875, \"count\": 1, \"min\": 0.8945975341796875, \"max\": 0.8945975341796875}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.0616982, \"EndTime\": 1665673038.0617557, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 6}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8393883666992188, \"count\": 1, \"min\": 0.8393883666992188, \"max\": 0.8393883666992188}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.062073, \"EndTime\": 1665673038.0621192, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 7}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9432586059570313, \"count\": 1, \"min\": 0.9432586059570313, \"max\": 0.9432586059570313}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.0624406, \"EndTime\": 1665673038.0624716, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 8}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.702761474609375, \"count\": 1, \"min\": 0.702761474609375, \"max\": 0.702761474609375}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.062808, \"EndTime\": 1665673038.062838, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 9}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.8147272338867187, \"count\": 1, \"min\": 0.8147272338867187, \"max\": 0.8147272338867187}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.063179, \"EndTime\": 1665673038.063207, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 10}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.9598355102539062, \"count\": 1, \"min\": 0.9598355102539062, \"max\": 0.9598355102539062}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.0635533, \"EndTime\": 1665673038.0635796, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 11}, \"Metrics\": {\"train_multiclass_cross_entropy_objective\": {\"sum\": 0.7322227783203125, \"count\": 1, \"min\": 0.7322227783203125, \"max\": 0.7322227783203125}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, epoch=14, train multiclass_cross_entropy_objective =0.9072907104492187\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:18.162] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 44, \"duration\": 81, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.1679623, \"EndTime\": 1665673038.1680286, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 0}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8905522801854588, \"count\": 1, \"min\": 0.8905522801854588, \"max\": 0.8905522801854588}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.1681564, \"EndTime\": 1665673038.1681788, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 1}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8593943140528224, \"count\": 1, \"min\": 0.8593943140528224, \"max\": 0.8593943140528224}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.1682425, \"EndTime\": 1665673038.1682613, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 2}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7685393599776534, \"count\": 1, \"min\": 0.7685393599776534, \"max\": 0.7685393599776534}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.1683168, \"EndTime\": 1665673038.1683335, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 3}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8112817025399423, \"count\": 1, \"min\": 0.8112817025399423, \"max\": 0.8112817025399423}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.1683886, \"EndTime\": 1665673038.1684058, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 4}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8814151523349522, \"count\": 1, \"min\": 0.8814151523349522, \"max\": 0.8814151523349522}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.1684582, \"EndTime\": 1665673038.1684752, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 5}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.880560522680884, \"count\": 1, \"min\": 0.880560522680884, \"max\": 0.880560522680884}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.1685264, \"EndTime\": 1665673038.1685436, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 6}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8240079450177716, \"count\": 1, \"min\": 0.8240079450177716, \"max\": 0.8240079450177716}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.1685967, \"EndTime\": 1665673038.1686134, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 7}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9287912179757883, \"count\": 1, \"min\": 0.9287912179757883, \"max\": 0.9287912179757883}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.168662, \"EndTime\": 1665673038.16868, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 8}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.679933771356806, \"count\": 1, \"min\": 0.679933771356806, \"max\": 0.679933771356806}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.168728, \"EndTime\": 1665673038.1687446, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 9}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.8714913033150338, \"count\": 1, \"min\": 0.8714913033150338, \"max\": 0.8714913033150338}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.1687925, \"EndTime\": 1665673038.1688077, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 10}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.9456884710638372, \"count\": 1, \"min\": 0.9456884710638372, \"max\": 0.9456884710638372}}}\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.168863, \"EndTime\": 1665673038.1688778, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"model\": 11}, \"Metrics\": {\"validation_multiclass_cross_entropy_objective\": {\"sum\": 0.7118841635214316, \"count\": 1, \"min\": 0.7118841635214316, \"max\": 0.7118841635214316}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, epoch=14, validation multiclass_cross_entropy_objective =0.8905522801854588\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=14, criteria=multiclass_cross_entropy_objective, value=0.679933771356806\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] Epoch 14: Loss improved. Updating best model\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] Saving model for epoch: 14\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] Saved checkpoint to \"/tmp/tmp2gtfdhip/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #progress_metric: host=algo-1, completed 100.0 % of epochs\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.0124135, \"EndTime\": 1665673038.1892421, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"epoch\": 14, \"Meta\": \"training_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 29416.0, \"count\": 1, \"min\": 29416, \"max\": 29416}, \"Total Batches Seen\": {\"sum\": 33.0, \"count\": 1, \"min\": 33, \"max\": 33}, \"Max Records Seen Between Resets\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Max Batches Seen Between Resets\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}, \"Reset Count\": {\"sum\": 17.0, \"count\": 1, \"min\": 17, \"max\": 17}, \"Number of Records Since Last Reset\": {\"sum\": 1776.0, \"count\": 1, \"min\": 1776, \"max\": 1776}, \"Number of Batches Since Last Reset\": {\"sum\": 2.0, \"count\": 1, \"min\": 2, \"max\": 2}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #throughput_metric: host=algo-1, train throughput=10018.390248822863 records/second\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 WARNING 140479147329344] wait_for_all_workers will not sync workers since the kv store is not running distributed\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 WARNING 140479147329344] wait_for_all_workers will not sync workers since the kv store is not running distributed\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:18.236] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 47, \"duration\": 15, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #early_stopping_criteria_metric: host=algo-1, epoch=14, criteria=multiclass_cross_entropy_objective, value=0.679933771356806\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:18.276] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/validation\", \"epoch\": 49, \"duration\": 27, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m/opt/amazon/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: VisibleDeprecationWarning: Creating an ndarray from nested sequences exceeding the maximum number of dimensions of 32 is deprecated. If you mean to do this, you must specify 'dtype=object' when creating the ndarray.\n", " return ufunc.reduce(obj, axis, dtype, out, **passkwargs)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #validation_score (algo-1) : ('multiclass_cross_entropy_objective', 0.679933771356806)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #validation_score (algo-1) : ('multiclass_accuracy', 0.8018018018018018)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #validation_score (algo-1) : ('multiclass_top_k_accuracy_3', 1.0)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #validation_score (algo-1) : ('dcg', 0.916824821953301)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #validation_score (algo-1) : ('macro_recall', 0.8032333)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #validation_score (algo-1) : ('macro_precision', 0.80768627)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #validation_score (algo-1) : ('macro_f_1.000', 0.8033984)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #validation_score (algo-1) : ('multiclass_balanced_accuracy', 0.8032332856758865)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #validation_score (algo-1) : ('multiclass_log_loss', 0.8713880263932385)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, validation multiclass_cross_entropy_objective =0.679933771356806\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, validation multiclass_accuracy =0.8018018018018018\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, validation multiclass_top_k_accuracy_3 =1.0\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, validation dcg =0.916824821953301\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, validation macro_recall =0.8032333254814148\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, validation macro_precision =0.8076862692832947\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, validation macro_f_1.000 =0.8033983707427979\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, validation multiclass_balanced_accuracy =0.8032332856758865\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, validation multiclass_log_loss =0.8713880263932385\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] Best model found for hyperparameters: {\"optimizer\": \"adam\", \"learning_rate\": 0.10200995219090397, \"l1\": 0.10587917499153388, \"wd\": 0.011994309302164696, \"lr_scheduler_step\": 52, \"lr_scheduler_factor\": 0.9835865984378375, \"lr_scheduler_minimum_lr\": 2.597459914786608e-06}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] Saved checkpoint to \"/tmp/tmpesms3zx2/mx-mod-0000.params\"\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:18.319] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/test\", \"epoch\": 0, \"duration\": 1593, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m[2022-10-13 14:57:18.360] [tensorio] [info] epoch_stats={\"data_pipeline\": \"/opt/ml/input/data/test\", \"epoch\": 1, \"duration\": 40, \"num_examples\": 1, \"num_bytes\": 11544}\u001b[0m\n", "\u001b[34m/opt/amazon/lib/python3.7/site-packages/numpy/core/fromnumeric.py:87: VisibleDeprecationWarning: Creating an ndarray from nested sequences exceeding the maximum number of dimensions of 32 is deprecated. If you mean to do this, you must specify 'dtype=object' when creating the ndarray.\n", " return ufunc.reduce(obj, axis, dtype, out, **passkwargs)\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673038.3192897, \"EndTime\": 1665673038.393034, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\", \"Meta\": \"test_data_iter\"}, \"Metrics\": {\"Total Records Seen\": {\"sum\": 222.0, \"count\": 1, \"min\": 222, \"max\": 222}, \"Total Batches Seen\": {\"sum\": 1.0, \"count\": 1, \"min\": 1, \"max\": 1}, \"Max Records Seen Between Resets\": {\"sum\": 222.0, \"count\": 1, \"min\": 222, \"max\": 222}, \"Max Batches Seen Between Resets\": {\"sum\": 1.0, \"count\": 1, \"min\": 1, \"max\": 1}, \"Reset Count\": {\"sum\": 1.0, \"count\": 1, \"min\": 1, \"max\": 1}, \"Number of Records Since Last Reset\": {\"sum\": 222.0, \"count\": 1, \"min\": 222, \"max\": 222}, \"Number of Batches Since Last Reset\": {\"sum\": 1.0, \"count\": 1, \"min\": 1, \"max\": 1}}}\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #test_score (algo-1) : ('multiclass_cross_entropy_objective', 0.8117860673784135)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #test_score (algo-1) : ('multiclass_accuracy', 0.7207207207207207)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #test_score (algo-1) : ('multiclass_top_k_accuracy_3', 1.0)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #test_score (algo-1) : ('dcg', 0.8821820095852688)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #test_score (algo-1) : ('macro_recall', 0.7169678)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #test_score (algo-1) : ('macro_precision', 0.7299402)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #test_score (algo-1) : ('macro_f_1.000', 0.7183555)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #test_score (algo-1) : ('multiclass_balanced_accuracy', 0.7169678147939017)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #test_score (algo-1) : ('multiclass_log_loss', 0.9070928323188799)\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, test multiclass_cross_entropy_objective =0.8117860673784135\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, test multiclass_accuracy =0.7207207207207207\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, test multiclass_top_k_accuracy_3 =1.0\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, test dcg =0.8821820095852688\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, test macro_recall =0.7169678211212158\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, test macro_precision =0.7299401760101318\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, test macro_f_1.000 =0.7183554768562317\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, test multiclass_balanced_accuracy =0.7169678147939017\u001b[0m\n", "\u001b[34m[10/13/2022 14:57:18 INFO 140479147329344] #quality_metric: host=algo-1, test multiclass_log_loss =0.9070928323188799\u001b[0m\n", "\u001b[34m#metrics {\"StartTime\": 1665673036.7212577, \"EndTime\": 1665673038.4023001, \"Dimensions\": {\"Algorithm\": \"Linear Learner\", \"Host\": \"algo-1\", \"Operation\": \"training\"}, \"Metrics\": {\"initialize.time\": {\"sum\": 183.4542751312256, \"count\": 1, \"min\": 183.4542751312256, \"max\": 183.4542751312256}, \"epochs\": {\"sum\": 15.0, \"count\": 1, \"min\": 15, \"max\": 15}, \"check_early_stopping.time\": {\"sum\": 15.160322189331055, \"count\": 16, \"min\": 0.23293495178222656, \"max\": 1.6911029815673828}, \"update.time\": {\"sum\": 1205.4119110107422, \"count\": 15, \"min\": 54.90374565124512, \"max\": 171.77414894104004}, \"finalize.time\": {\"sum\": 124.60732460021973, \"count\": 1, \"min\": 124.60732460021973, \"max\": 124.60732460021973}, \"setuptime\": {\"sum\": 4.802703857421875, \"count\": 1, \"min\": 4.802703857421875, \"max\": 4.802703857421875}, \"totaltime\": {\"sum\": 1919.2438125610352, \"count\": 1, \"min\": 1919.2438125610352, \"max\": 1919.2438125610352}}}\u001b[0m\n", "\n", "2022-10-13 14:57:54 Completed - Training job completed\n", "ProfilerReport-1665672773: NoIssuesFound\n", "Training seconds: 178\n", "Billable seconds: 178\n" ] } ], "source": [ "multiclass_estimator.fit([train_records, val_records, test_records])" ] }, { "cell_type": "markdown", "id": "919caf7e", "metadata": { "id": "cfcb1f00-4ba1-499b-a80f-67de7d34ead2" }, "source": [ "### Deploy a model hosting endpoint" ] }, { "cell_type": "code", "execution_count": 22, "id": "ac9729f2", "metadata": { "id": "bd9fac51-c7b2-4b0c-bf6b-c264a6e82c03" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "--------!" ] } ], "source": [ "multiclass_predictor = multiclass_estimator.deploy(initial_instance_count=1, instance_type='ml.m4.xlarge')" ] }, { "cell_type": "markdown", "id": "f77a04cc", "metadata": { "id": "d5274955-f1a9-4a94-ba1f-b67b687c5286" }, "source": [ "### Evaluate a model on a test set using the given prediction endpoint. Display classification metrics" ] }, { "cell_type": "code", "execution_count": 23, "id": "f0ca1fa2", "metadata": { "id": "f4951683-c2b1-44a8-9d53-4576b17dc8a8" }, "outputs": [], "source": [ "def evaluate_metrics(predictor, test_features, test_labels):\n", " # split the test dataset into 100 batches and evaluate using prediction endpoint\n", " prediction_batches = [predictor.predict(batch) for batch in np.array_split(test_features, 100)]\n", "\n", " # parse protobuf responses to extract predicted labels\n", " extract_label = lambda x: x.label['predicted_label'].float32_tensor.values\n", " test_preds = np.concatenate([np.array([extract_label(x) for x in batch]) for batch in prediction_batches])\n", " test_preds = test_preds.reshape((-1,))\n", " \n", " # calculate accuracy\n", " accuracy = (test_preds == test_labels).sum() / test_labels.shape[0]\n", " \n", " # calculate recall for each class\n", " recall_per_class, classes = [], []\n", " for target_label in np.unique(test_labels):\n", " recall_numerator = np.logical_and(test_preds == target_label, test_labels == target_label).sum()\n", " recall_denominator = (test_labels == target_label).sum()\n", " recall_per_class.append(recall_numerator / recall_denominator)\n", " classes.append(label_map[target_label])\n", " recall = pd.DataFrame({'recall': recall_per_class, 'class_label': classes})\n", " recall.sort_values('class_label', ascending=False, inplace=True)\n", "\n", " # calculate confusion matrix\n", " label_mapper = np.vectorize(lambda x: label_map[x])\n", " confusion_matrix = pd.crosstab(label_mapper(test_labels), label_mapper(test_preds), \n", " rownames=['Actuals'], colnames=['Predictions'], normalize='index')\n", "\n", " # display results\n", " sns.heatmap(confusion_matrix, annot=True, fmt='.2f', cmap=\"YlGnBu\").set_title('Confusion Matrix') \n", " ax = recall.plot(kind='barh', x='class_label', y='recall', color='steelblue', title='Recall', legend=False)\n", " ax.set_ylabel('')\n", " print('Accuracy: {:.3f}'.format(accuracy))" ] }, { "cell_type": "markdown", "id": "f57b7232", "metadata": { "id": "0c9ac589-ffe4-443f-999b-7d5eb4f6073a" }, "source": [ "### Evaluate metrics of the model trained with default hyperparameters" ] }, { "cell_type": "code", "execution_count": 24, "id": "67ecb951", "metadata": { "id": "32f913fd-4528-4c54-9261-ea492d975565" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy: 0.721\n" ] }, { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "evaluate_metrics(multiclass_predictor, test_features, test_labels)" ] }, { "cell_type": "markdown", "id": "09cc1785", "metadata": { "id": "17b27e9c-a3b1-49e0-8dcd-968a43dd2549" }, "source": [ "### Copy the SageMaker endpoint name from SageMaker console using the documentation and proceed with next steps." ] }, { "cell_type": "markdown", "id": "592c3f8c", "metadata": { "id": "e485b237-d951-402c-8f98-d85ae75836e6" }, "source": [ "In this Notebook, we have learnt how to predict Risk Index using multiclass classifier SageMaker Models. How to build, run and evaluate them in Watson Studio platform. This model is now deployed on SageMaker Platform." ] }, { "cell_type": "code", "execution_count": null, "id": "cf3e833a", "metadata": { "id": "049294fc-09af-41cc-84e7-a575f623e212" }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3.9", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.7" } }, "nbformat": 4, "nbformat_minor": 5 }