diff --git a/config.json b/config.json
index c11de6c..1804e72 100644
--- a/config.json
+++ b/config.json
@@ -5,8 +5,8 @@
     "sans-serif",
     "serif"
   ],
-  "training_set": 20000,
-  "testing_set": 500,
+  "training_set": 2000,
+  "testing_set": 1000,
   "image_size": 16,
   "threshold": 400,
   "network": {
diff --git a/examples/0123456789.png b/examples/0123456789.png
index 3752051..7bba065 100644
Binary files a/examples/0123456789.png and b/examples/0123456789.png differ
diff --git a/main.js b/main.js
index 29a16be..887c393 100644
--- a/main.js
+++ b/main.js
@@ -1,14 +1,7 @@
-<<<<<<< HEAD
-(function (log) {
-  'use strict';
-
-  log('reading config file ...');
-=======
 (function () {
   'use strict';
 
   console.log('reading config file ...');
->>>>>>> softmax
 
   var synaptic = require('synaptic'),
       network = require('./network.js'),
@@ -29,131 +22,6 @@
   config.fonts = config.fonts || ['serif', 'sans-serif'];
   config.distortion = config.distortion === undefined ? true : config.distortion;
   config.network.hidden = config.network.hidden || 40;
-<<<<<<< HEAD
-  config.network.output = config.network.output || 8;
-  config.network.learning_rate = config.network.learning_rate || 0.1;
-
-  log('... done');
-  log();
-
-  var perceptron;
-
-  if(config.mnist === true) {
-    perceptron = new synaptic.Architect.Perceptron(
-      (config.image_size * config.image_size), // input
-      config.network.hidden, // hidden
-      4 // output
-    );
-
-    mnist();
-  } else {
-    perceptron = new synaptic.Architect.Perceptron(
-      (config.image_size * config.image_size), // input
-      config.network.hidden, // hidden
-      config.network.output // output
-    );
-
-    var index,
-        samples = config.training_set + config.testing_set,
-        training = [],
-        testing = [],
-        settings = {
-          size: config.text.length,
-          height: config.image_size,
-          text: config.text,
-          fonts: config.fonts,
-          distortion: config.distortion
-        };
-
-    log('generating images ...');
-
-    for(index = 0; index < samples; index++)
-      captcha.generate(settings, generate(index));
-  }
-
-  // captcha callback
-  function generate(index) {
-    return function(text, data) {
-      var png = new PNG({ filterType: 4 });
-      png.parse(data, parse(text, index));
-
-      if(index === 0)
-        fs.writeFileSync('./examples/' + text + '.png', data, 'base64');
-    };
-  }
-
-  // parse MNIST data
-  function mnist() {
-    log('parsing MNIST data ...');
-
-    var data = fs.readFileSync('./mnist/train-images.idx3-ubyte'),
-        labels = fs.readFileSync('./mnist/train-labels.idx1-ubyte'),
-        training = [],
-        testing = [],
-        pixels = [],
-        image,
-        x, y;
-
-    config.training_set = 60000;
-    config.testing_set = 10000;
-    config.threshold = 50;
-    config.image_size = 20;
-
-    for(image = 0; image < config.training_set; image++) {
-      for(y = 4; y < config.image_size + 4; y++)
-        for(x = 4; x < config.image_size + 4; x++)
-          pixels.push(data[(image * 28 * 28) + (x + (y * 28)) + 15]);
-
-      pixels = tools.center(
-        pixels.map(function(pixel) {
-          return pixel > config.threshold ? 1 : 0;
-        })
-      );
-
-      training.push({
-        input: pixels,
-        output: ('0000' + parseInt(labels[image + 8]).toString(2)).substr(-4).split('').map(Number)
-      });
-
-      pixels = [];
-    }
-
-    data = fs.readFileSync('./mnist/t10k-images-2.idx3-ubyte');
-    labels = fs.readFileSync('./mnist/t10k-labels.idx1-ubyte');
-
-    for(image = 0; image < config.testing_set; image++) {
-      for(y = 4; y < config.image_size + 4; y++)
-        for(x = 4; x < config.image_size + 4; x++)
-          pixels.push(data[(image * 28 * 28) + (x + (y * 28)) + 15]);
-
-      pixels = tools.center(
-        pixels.map(function(pixel) {
-          return pixel > config.threshold ? 1 : 0;
-        })
-      );
-
-      testing.push({
-        input: pixels,
-        output: ('0000' + parseInt(labels[image + 8]).toString(2)).substr(-4).split('').map(Number)
-      });
-
-      pixels = [];
-    }
-
-    log('... done', '\n');
-
-    tools.validate(perceptron, training);
-    tools.validate(perceptron, testing);
-
-    network.train(perceptron, training, config.network.learning_rate);
-    fs.writeFileSync('./ocr.js', perceptron.standalone().toString());
-    network.test(perceptron, testing);
-  }
-
-  // 'parsed' event callback
-  function parse(text, index) {
-    return function(error, data) {
-=======
   config.network.output = config.network.output || 10;
   config.network.learning_rate = config.network.learning_rate || 0.1;
 
@@ -187,18 +55,13 @@
     var png = new PNG({ filterType: 4 });
 
     png.parse(data, function(error, data) {
->>>>>>> softmax
       if(error)
         throw error;
 
       var position,
           chunk = [],
           pixel = [],
-<<<<<<< HEAD
-          i, j, k, x, y;
-=======
           i, j, x, y;
->>>>>>> softmax
 
       for(i = 0; i < config.text.length; i++) {
         for(y = 0; y < data.height; y++) {
@@ -222,11 +85,7 @@
         var output = Array.apply(null, new Array(config.network.output)).map(Number.prototype.valueOf, 0);
         output[i] = 1;
 
-<<<<<<< HEAD
-        if(index < config.training_set) {
-=======
         if(k < config.training_set) {
->>>>>>> softmax
           training.push({
             input: chunk,
             output: output
@@ -241,15 +100,9 @@
         chunk = [];
       }
 
-<<<<<<< HEAD
-      if(index === samples - 1) {
-        log('... done');
-        log();
-=======
       if(k++ === samples - 1) {
         console.log('... done');
         console.log();
->>>>>>> softmax
 
         network.train(perceptron, training, config.network.learning_rate);
         fs.writeFileSync('./ocr.js', 'module.exports = ' + perceptron.standalone().toString());
@@ -257,13 +110,9 @@
       }
     });
   }
-<<<<<<< HEAD
-})(console.log);
-=======
 
   console.log('generating images ...');
 
   for(index = 0; index < samples; index++)
     captcha.generate(settings, generate);
 })();
->>>>>>> softmax