335 lines
11 KiB
Plaintext
335 lines
11 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"<div class=\"alert alert-block alert-info\">\n",
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"<h1> Modelowanie Języka</h1>\n",
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"<h2> 12. <i>Model neuronowy rekurencyjny</i> [ćwiczenia]</h2> \n",
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"<h3> Jakub Pokrywka (2022)</h3>\n",
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"</div>\n",
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"\n",
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""
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Ensemble modeli"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"W jaki sposób można podnieść wynik predykcji dla zadania uczenia maszynowego?"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 32,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"mkdir: cannot create directory ‘dev-0-ireland-news’: File exists\r\n"
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]
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}
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],
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"source": [
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"!mkdir dev-0-ireland-news"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Mamy wyzwanie:"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"https://gonito.net/challenge-all-submissions/ireland-news-headlines-word-gap"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"https://github.com/kubapok/ireland-news-word-gap/tree/0c6557c8a3cd6d8c77f64618850b2ae82c19476a"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 33,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"--2022-05-13 13:23:05-- https://github.com/kubapok/ireland-news-word-gap/raw/11c72875023c5c01c9d0c0ca39d72c90c840aeb3/dev-0/out.tsv\n",
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"Resolving github.com (github.com)... 140.82.121.4\n",
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"Connecting to github.com (github.com)|140.82.121.4|:443... connected.\n",
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"HTTP request sent, awaiting response... 302 Found\n",
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"Location: https://raw.githubusercontent.com/kubapok/ireland-news-word-gap/11c72875023c5c01c9d0c0ca39d72c90c840aeb3/dev-0/out.tsv [following]\n",
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"--2022-05-13 13:23:06-- https://raw.githubusercontent.com/kubapok/ireland-news-word-gap/11c72875023c5c01c9d0c0ca39d72c90c840aeb3/dev-0/out.tsv\n",
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"Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.110.133, 185.199.111.133, 185.199.108.133, ...\n",
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"Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.110.133|:443... connected.\n",
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"HTTP request sent, awaiting response... 200 OK\n",
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"Length: 63249692 (60M) [text/plain]\n",
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"Saving to: ‘out.tsv’\n",
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"\n",
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"out.tsv 100%[===================>] 60,32M 26,7MB/s in 2,3s \n",
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"\n",
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"2022-05-13 13:23:08 (26,7 MB/s) - ‘out.tsv’ saved [63249692/63249692]\n",
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"\n",
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"--2022-05-13 13:23:09-- https://github.com/kubapok/ireland-news-word-gap/raw/0c6557c8a3cd6d8c77f64618850b2ae82c19476a/dev-0/out.tsv\n",
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"Resolving github.com (github.com)... 140.82.121.4\n",
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"Connecting to github.com (github.com)|140.82.121.4|:443... connected.\n",
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"HTTP request sent, awaiting response... 302 Found\n",
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"Location: https://raw.githubusercontent.com/kubapok/ireland-news-word-gap/0c6557c8a3cd6d8c77f64618850b2ae82c19476a/dev-0/out.tsv [following]\n",
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"--2022-05-13 13:23:09-- https://raw.githubusercontent.com/kubapok/ireland-news-word-gap/0c6557c8a3cd6d8c77f64618850b2ae82c19476a/dev-0/out.tsv\n",
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"Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.110.133, 185.199.111.133, 185.199.108.133, ...\n",
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"Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.110.133|:443... connected.\n",
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"HTTP request sent, awaiting response... 200 OK\n",
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"Length: 63271863 (60M) [text/plain]\n",
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"Saving to: ‘out.tsv’\n",
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"\n",
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"out.tsv 100%[===================>] 60,34M 45,1MB/s in 1,3s \n",
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"\n",
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"2022-05-13 13:23:10 (45,1 MB/s) - ‘out.tsv’ saved [63271863/63271863]\n",
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"\n",
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"--2022-05-13 13:23:11-- https://git.wmi.amu.edu.pl/kubapok/ireland-news-word-gap-prediction/raw/branch/master/dev-0/expected.tsv\n",
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"Resolving git.wmi.amu.edu.pl (git.wmi.amu.edu.pl)... 150.254.78.40\n",
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"Connecting to git.wmi.amu.edu.pl (git.wmi.amu.edu.pl)|150.254.78.40|:443... connected.\n",
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"HTTP request sent, awaiting response... 200 OK\n",
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"Length: 866583 (846K) [text/plain]\n",
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"Saving to: ‘expected.tsv.1’\n",
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"\n",
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"expected.tsv.1 100%[===================>] 846,27K 1,91MB/s in 0,4s \n",
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"\n",
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"2022-05-13 13:23:11 (1,91 MB/s) - ‘expected.tsv.1’ saved [866583/866583]\n",
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"\n"
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]
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}
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],
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"source": [
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"!wget https://github.com/kubapok/ireland-news-word-gap/raw/11c72875023c5c01c9d0c0ca39d72c90c840aeb3/dev-0/out.tsv\n",
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"!mv out.tsv ./dev-0/out-solution1.tsv\n",
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"!wget https://github.com/kubapok/ireland-news-word-gap/raw/0c6557c8a3cd6d8c77f64618850b2ae82c19476a/dev-0/out.tsv\n",
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"!mv out.tsv ./dev-0/out-solution2.tsv\n",
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"! ( cd dev-0 ; wget https://git.wmi.amu.edu.pl/kubapok/ireland-news-word-gap-prediction/raw/branch/master/dev-0/expected.tsv)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 34,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"--2022-05-13 13:23:12-- https://gonito.net/get/bin/geval\n",
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"Resolving gonito.net (gonito.net)... 150.254.78.126\n",
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"Connecting to gonito.net (gonito.net)|150.254.78.126|:443... connected.\n",
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"HTTP request sent, awaiting response... 200 OK\n",
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"Length: 12860136 (12M) [application/octet-stream]\n",
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"Saving to: ‘geval.1’\n",
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"\n",
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"geval.1 100%[===================>] 12,26M 2,67MB/s in 4,1s \n",
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"\n",
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"2022-05-13 13:23:16 (2,97 MB/s) - ‘geval.1’ saved [12860136/12860136]\n",
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"\n"
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]
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}
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],
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"source": [
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"!wget https://gonito.net/get/bin/geval\n",
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"!chmod u+x geval"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 35,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"35.05218788086649\r\n"
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]
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}
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],
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"source": [
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"!./geval --metric PerplexityHashed -o ./dev-0/out-solution1.tsv -e dev-0/expected.tsv"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 36,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"33.47429048442195\r\n"
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]
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}
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],
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"source": [
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"!./geval --metric PerplexityHashed -o ./dev-0/out-solution2.tsv -e dev-0/expected.tsv"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 37,
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"metadata": {},
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"outputs": [],
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"source": [
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"with open('./dev-0/out-solution1.tsv') as s1, open('./dev-0/out-solution2.tsv') as s2, open('./dev-0/out-merge.tsv','w') as f_merge:\n",
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" for l1, l2 in zip(s1, s2):\n",
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" dir1 = {''.join(x.split(':')[:-1]): float(x.split(':')[-1]) for x in l1.rstrip().split(' ')}\n",
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" dir2 = {''.join(x.split(':')[:-1]): float(x.split(':')[-1]) for x in l2.rstrip().split(' ')}\n",
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" newdir = dict()\n",
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" for k in dir1.keys() | dir2.keys():\n",
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" newdir[k] = dir1[k] if k in dir1 else 0.0\n",
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" newdir[k] += dir2[k] if k in dir2 else 0.0\n",
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" newdir[k] /= 2\n",
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" merge_line = ' '.join([k + ':' + str(v) for k,v in newdir.items()]) + '\\n'\n",
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" f_merge.write(merge_line)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 38,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"29.054162509715063\r\n"
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]
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}
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],
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"source": [
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"!./geval --metric PerplexityHashed -o ./dev-0/out-merge.tsv -e dev-0/expected.tsv"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Złożenie:\n",
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"\n",
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"- kilku dobrych niezależnych modeli \n",
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"- kilku modeli wytrenowanych dla różnego seeda\n",
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"- kilku ostatnich checkpointów"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"W jaki sposób składać różne modele:\n",
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"\n",
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"- średnia ważona\n",
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"- średnia geometryczna\n",
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"- inna średnia\n",
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"- trenowanie osobnego prostego modelu, którego zadanie to składanie modeli (np. regresja liniowa)\n",
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"\n",
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"\n",
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"Można też trenować wspólnie kilka modeli jednocześnie ze wspólnym backpropagation."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Jakie są minusy ensemble?\n",
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"\n",
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"- wyższy stopień skomplikowania modelu\n",
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"- dłuższy czas inferencji\n",
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"- zużycie większych zasobów komputera\n",
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"- gorsza interpretowalność"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"W praktyce jeżeli startujemy w konkursie uczenia maszynowego, zawsze warto robić ensemble.\n",
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"\n",
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"\n",
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"W komercji jeżeli mamy ograniczenia czasowe lub zasobów, model jest ciężki, wynik modelu nie jest bardzo ważny, to często nie korzysta się z ensembli.\n",
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"W nauce albo kiedy chcemy porównać kilka różnych metod, to składanie modeli zaburza nam niepotrzebnie obraz."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Warto mieć na uwadze, że niektóre metody z założenia są ensemblami. Np. las losowy albo boostowane drzewa decyzyjne."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### ZADANIE\n",
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"\n",
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"przykładowy tekst: \"ala\" \"ma\" \"kota\" \"MASK\" \"2\" \"psy\" \"i\" \"chomika\"\n",
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"\n",
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"Stworzyć 2 sieci rekurencyjne LSTM dla Challenging America word-gap prediction. \n",
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"- jedna sieć powinna działać do przodu (czyli jak zwyczajna sieć): \"ala\" \"ma\" \"kota\"\n",
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"- druga siec powinna działać do tyłu: \"chomika\" \"i\" \"psy\" \"2\"\n",
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" \n",
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"Zrobienie sieci odwrotnej jest bardzo proste. Wystarczy odwrócić kolejność słów, nie ma potrzeby ingerować w architekturę modeli.\n",
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"\n",
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"Następnie należy zrobić jakiś ensemble tych modeli. W najprostszej wersji może to być średnia arytmetyczna. Warto jednak spróbować innych sposobów, np. można trenować te sieci łącznie.\n",
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"\n",
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"\n",
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"Wymogi takie jak zawsze, zadanie widoczne na gonito."
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]
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}
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],
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"metadata": {
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"author": "Jakub Pokrywka",
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"email": "kubapok@wmi.amu.edu.pl",
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"lang": "pl",
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.3"
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},
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"subtitle": "0.Informacje na temat przedmiotu[ćwiczenia]",
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"title": "Ekstrakcja informacji",
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"year": "2021"
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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