NLP-93%-4s-750samples.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     C:\\Users\\user\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n",
      "[nltk_data] Downloading package punkt to\n",
      "[nltk_data]     C:\\Users\\user\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package punkt is already up-to-date!\n",
      "[nltk_data] Downloading package wordnet to\n",
      "[nltk_data]     C:\\Users\\user\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package wordnet is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from nltk.tokenize import sent_tokenize, word_tokenize\n",
    "from nltk import pos_tag\n",
    "from nltk.stem import PorterStemmer\n",
    "from nltk import WordNetLemmatizer\n",
    "from nltk.corpus import movie_reviews\n",
    "from nltk.corpus import stopwords\n",
    "import sentencepiece\n",
    "import nltk\n",
    "nltk.download('stopwords')\n",
    "from collections import Counter\n",
    "import pandas\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import os \n",
    "from sklearn.metrics import classification_report\n",
    "from transformers import TFAlbertModel\n",
    "from transformers import TFRobertaModel\n",
    "from transformers import TFDistilBertModel\n",
    "from transformers import AlbertTokenizer\n",
    "from transformers import RobertaTokenizer\n",
    "from transformers import DistilBertTokenizer\n",
    "import glob\n",
    "from transformers import *\n",
    "nltk.download('punkt')\n",
    "nltk.download('wordnet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import patoolib\n",
    "import os\n",
    "\n",
    "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'\n",
    "import warnings  # To ignore any warnings\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "import os\n",
    "import glob\n",
    "import numpy as np\n",
    "import itertools\n",
    "import pandas as pd\n",
    "\n",
    "# Audio\n",
    "import librosa\n",
    "import librosa.display\n",
    "\n",
    "# Scikit learn\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import classification_report, accuracy_score, confusion_matrix\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.utils import shuffle\n",
    "from sklearn.utils import class_weight\n",
    "\n",
    "# Keras\n",
    "import keras\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense, Dropout, Activation, Flatten\n",
    "from keras.layers import Convolution2D, Conv2D, MaxPooling2D, GlobalAveragePooling2D\n",
    "from keras.utils import to_categorical\n",
    "import warnings"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\finish\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\georgian\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\greek\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\hungarian\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\japanese\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\ltalian\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\slovenian\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\swedish\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\thai\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\viatnamese\n",
      "dlzina na dataset:  7510\n"
     ]
    }
   ],
   "source": [
    "INPUT_DIR = 'D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset/**'\n",
    " \n",
    "dataset = []\n",
    "for filename in glob.iglob(INPUT_DIR):\n",
    "    kolkuPoKlasa=0\n",
    "    print(filename)\n",
    "    for f in glob.iglob(filename+'/**'):\n",
    "        \n",
    "        if (kolkuPoKlasa>750):\n",
    "            kolkuPoKlasa=0\n",
    "            break\n",
    "        if os.path.exists(f):\n",
    "            label = os.path.basename(filename)\n",
    "            duration = librosa.get_duration(filename=f)\n",
    "            #print('label', f, 'duration', duration)\n",
    "            # skip audio smaller than 2 secs\n",
    "            if duration >= 4:\n",
    "                kolkuPoKlasa+=1\n",
    "                #slice_size = 3\n",
    "                #iterations = int((duration - slice_size) / (slice_size - 1))\n",
    "                iterations = 1\n",
    "                #initial_offset = (duration - ((iterations * (slice_size - 1)) + 1)) / 2\n",
    "                for i in range(iterations):\n",
    "                    #offset = initial_offset + i * (slice_size - 1)\n",
    "                    offset = 0\n",
    "                    if (label == \"finish\"):\n",
    "                        dataset.append({\n",
    "                            \"filename\": f,\n",
    "                            \"label\": \"finish\",\n",
    "                            \"offset\": offset\n",
    "                        })\n",
    "                    elif (label == \"georgian\"):\n",
    "                        dataset.append({\n",
    "                            \"filename\": f,\n",
    "                            \"label\": \"georgian\",\n",
    "                            \"offset\": offset\n",
    "                        })\n",
    "                    elif (label == \"hungarian\"):\n",
    "                        dataset.append({\n",
    "                            \"filename\": f,\n",
    "                            \"label\": \"hungarian\",\n",
    "                            \"offset\": offset\n",
    "                        })\n",
    "                    elif (label == \"japanese\"):\n",
    "                        dataset.append({\n",
    "                            \"filename\": f,\n",
    "                            \"label\": \"japanese\",\n",
    "                            \"offset\": offset\n",
    "                        })\n",
    "                    elif (label == \"ltalian\"):\n",
    "                        dataset.append({\n",
    "                            \"filename\": f,\n",
    "                            \"label\": \"ltalian\",\n",
    "                            \"offset\": offset\n",
    "                        })\n",
    "                    elif (label == \"slovenian\"):\n",
    "                        dataset.append({\n",
    "                            \"filename\": f,\n",
    "                            \"label\": \"slovenian\",\n",
    "                            \"offset\": offset\n",
    "                        })\n",
    "                    elif (label == \"swedish\"):\n",
    "                        dataset.append({\n",
    "                            \"filename\": f,\n",
    "                            \"label\": \"swedish\",\n",
    "                            \"offset\": offset\n",
    "                        })\n",
    "                    elif (label == \"thai\"):\n",
    "                        dataset.append({\n",
    "                            \"filename\": f,\n",
    "                            \"label\": \"thai\",\n",
    "                            \"offset\": offset\n",
    "                        })\n",
    "                    elif (label == \"greek\"):\n",
    "                        dataset.append({\n",
    "                            \"filename\": f,\n",
    "                            \"label\": \"greek\",\n",
    "                            \"offset\": offset\n",
    "                        })\n",
    "                    else:\n",
    "                        dataset.append({\n",
    "                            \"filename\": f,\n",
    "                            \"label\": \"viatnamese\",\n",
    "                            \"offset\": offset\n",
    "                        })\n",
    "        \n",
    "print('dlzina na dataset: ',len(dataset))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7510  pred\n"
     ]
    },
    {
     "ename": "AttributeError",
     "evalue": "'list' object has no attribute 'filename'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-44-9948aa0afe71>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0mnuli\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdataset\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m   \u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0msr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlibrosa\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdataset\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfilename\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mduration\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      6\u001b[0m   \u001b[1;32mif\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0many\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      7\u001b[0m     \u001b[0mnuli\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'list' object has no attribute 'filename'"
     ]
    }
   ],
   "source": [
    "print(len(dataset),' pred')\n",
    "# naoganje i brishenje na prazni samples\n",
    "nuli = []\n",
    "for i in range(0,len(dataset)):\n",
    "  y,sr = librosa.load(dataset.filename.iloc[i], duration=4)\n",
    "  if y.any() == 0:\n",
    "    nuli.append(i)\n",
    "print(nuli)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = dataset.drop(index=nuli)\n",
    "print('po izbrisheni dolzijna',len(dataset))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 7510 entries, 4458 to 7270\n",
      "Data columns (total 3 columns):\n",
      "filename    7510 non-null object\n",
      "label       7510 non-null object\n",
      "offset      7510 non-null int64\n",
      "dtypes: int64(1), object(2)\n",
      "memory usage: 234.7+ KB\n"
     ]
    }
   ],
   "source": [
    "dataset = pd.DataFrame(dataset)\n",
    "dataset = shuffle(dataset, random_state=42)\n",
    "dataset.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "train, test = train_test_split(dataset, test_size=0.2, random_state=42)\n",
    "x_train = []\n",
    "x_test = []\n",
    "x_val = []\n",
    "\n",
    "encoder = LabelEncoder()\n",
    "encoder.fit(train.label)\n",
    "\n",
    "y_train = encoder.transform(train.label)\n",
    "\n",
    "y_test =  encoder.transform(test[:int(len(test)*0.5)].label)\n",
    "y_val =   encoder.transform(test[int(len(test)*0.5):].label)\n",
    "\n",
    "for idx in range(len(train)):\n",
    "    x_train.append(extract_features(train.filename.iloc[idx], train.offset.iloc[idx]))\n",
    "\n",
    "# 10 % test data\n",
    "for idx in range(0,len(test)//2):\n",
    "    x_test.append(extract_features(test.filename.iloc[idx], test.offset.iloc[idx]))\n",
    "    \n",
    "\n",
    "# 10% val data\n",
    "for idx in range(len(test)//2,len(test)):\n",
    "    x_val.append(extract_features(test.filename.iloc[idx], test.offset.iloc[idx]))\n",
    "    \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X train: (6008, 40, 173, 1)\n",
      "Y train: (6008, 10)\n",
      "X test: (751, 40, 173, 1)\n",
      "Y test: (751, 10)\n",
      "X validation: (751, 40, 173, 1)\n",
      "Y validation: (751, 10)\n",
      "[1.02525597 0.9865353  0.99141914 1.0097479  1.00636516 0.98815789\n",
      " 1.02003396 0.97850163 0.99305785 1.00300501]\n"
     ]
    }
   ],
   "source": [
    "x_test = np.asarray(x_test)\n",
    "x_val = np.asarray(x_val)\n",
    "x_train = np.asarray(x_train)\n",
    "\n",
    "\n",
    "    # Compute class weights\n",
    "class_weights = class_weight.compute_class_weight('balanced', np.unique(y_train), y_train)\n",
    "    #test\n",
    "#class_weights = {i: class_weights[i] for i in range(len(class_weights))}\n",
    "    #test\n",
    "x_train = x_train.reshape(x_train.shape[0], x_train.shape[1], x_train.shape[2], 1)\n",
    "x_test = x_test.reshape(x_test.shape[0], x_test.shape[1], x_test.shape[2], 1)\n",
    "x_val = x_val.reshape(x_val.shape[0], x_val.shape[1], x_val.shape[2], 1)\n",
    "y_train = to_categorical(y_train)\n",
    "y_test = to_categorical(y_test)\n",
    "y_val = to_categorical(y_val)\n",
    "\n",
    "print(\"X train:\", x_train.shape)\n",
    "print(\"Y train:\", y_train.shape)\n",
    "print(\"X test:\", x_test.shape)\n",
    "print(\"Y test:\", y_test.shape)\n",
    "\n",
    "print(\"X validation:\", x_val.shape)\n",
    "print(\"Y validation:\", y_val.shape)\n",
    "\n",
    "print(class_weights)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Extract MFCC from spectogram\n",
    "def extract_features(audio_path, offset):\n",
    "    y, sr = librosa.load(audio_path, offset=offset, duration=4.0)\n",
    "\n",
    "    S = librosa.feature.melspectrogram(y, sr=sr, n_fft=2048,\n",
    "                                       hop_length=512,\n",
    "                                       n_mels=128)\n",
    "    mfccs = librosa.feature.mfcc(S=librosa.power_to_db(S), n_mfcc=40)\n",
    "\n",
    "    return mfccs\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib\n",
    "matplotlib.rcParams['figure.figsize'] = (14, 5)\n",
    "matplotlib.rcParams['font.size'] = 12\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "num_classes = 10\n",
    "class_counts = dataset.label.value_counts()\n",
    "cmap = plt.cm.get_cmap(plt.cm.Set3, 10)\n",
    "colors = [cmap(i) for i in range(num_classes)]\n",
    "plt.barh(range(num_classes)[::-1], class_counts, tick_label=dataset.label.unique(),\n",
    "         color=colors)\n",
    "plt.title('Class distribution of dataset')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\ltalian\\common_voice_lt_23717844.mp3\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\swedish\\common_voice_sv-SE_19173578.mp3\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\slovenian\\common_voice_sl_17568689.mp3\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\georgian\\common_voice_ka_21356969.mp3\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\finish\\common_voice_fi_23874846.mp3\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\hungarian\\common_voice_hu_23549374.mp3\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\japanese\\common_voice_ja_19485593.mp3\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\viatnamese\\common_voice_vi_23392017.mp3\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\greek\\common_voice_el_20432953.mp3\n",
      "D:/studies7/Natural_Language_processing/MAIN_PROJECT/dataset\\thai\\common_voice_th_23650628.mp3\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x360 with 30 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "idx = 0\n",
    "for label in dataset.label.unique():    \n",
    "    y, sr = librosa.load(dataset[dataset.label==label].filename.iloc[3], duration=4)\n",
    "    print(dataset[dataset.label==label].filename.iloc[3])\n",
    "    \n",
    "    # Wave plot\n",
    "    idx+=1\n",
    "    \n",
    "    plt.subplot(10, 3, idx)\n",
    "    plt.title(\"%s waveplot\" % label)\n",
    "    librosa.display.waveplot(y, sr=sr)\n",
    "\n",
    "    # Mel Spectrogram\n",
    "    idx+=1\n",
    "    plt.subplot(10, 3, idx)\n",
    "    S = librosa.feature.melspectrogram(y, sr=sr, n_fft=2048, hop_length=512, n_mels=128)\n",
    "    S_DB = librosa.power_to_db(S, ref=np.max)\n",
    "    librosa.display.specshow(S_DB, sr=sr, hop_length=512, x_axis='time', y_axis='mel')\n",
    "    plt.title(\"%s mel spectogram\" % label)\n",
    "\n",
    "    # MFCC (Mel spectrogram)\n",
    "    idx+=1\n",
    "    mfccs = librosa.feature.mfcc(S=librosa.power_to_db(S), n_mfcc=40)\n",
    "    plt.subplot(10, 3, idx)\n",
    "    librosa.display.specshow(mfccs, x_axis='time')\n",
    "    plt.title(\"%s mfcc(Mel Spectrogram)\" % label)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_3\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_9 (Conv2D)            (None, 39, 172, 16)       80        \n",
      "_________________________________________________________________\n",
      "max_pooling2d_9 (MaxPooling2 (None, 19, 86, 16)        0         \n",
      "_________________________________________________________________\n",
      "dropout_9 (Dropout)          (None, 19, 86, 16)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_10 (Conv2D)           (None, 18, 85, 32)        2080      \n",
      "_________________________________________________________________\n",
      "max_pooling2d_10 (MaxPooling (None, 9, 42, 32)         0         \n",
      "_________________________________________________________________\n",
      "dropout_10 (Dropout)         (None, 9, 42, 32)         0         \n",
      "_________________________________________________________________\n",
      "conv2d_11 (Conv2D)           (None, 8, 41, 64)         8256      \n",
      "_________________________________________________________________\n",
      "max_pooling2d_11 (MaxPooling (None, 4, 20, 64)         0         \n",
      "_________________________________________________________________\n",
      "dropout_11 (Dropout)         (None, 4, 20, 64)         0         \n",
      "_________________________________________________________________\n",
      "conv2d_12 (Conv2D)           (None, 3, 19, 128)        32896     \n",
      "_________________________________________________________________\n",
      "max_pooling2d_12 (MaxPooling (None, 1, 9, 128)         0         \n",
      "_________________________________________________________________\n",
      "dropout_12 (Dropout)         (None, 1, 9, 128)         0         \n",
      "_________________________________________________________________\n",
      "global_average_pooling2d_3 ( (None, 128)               0         \n",
      "_________________________________________________________________\n",
      "dense_3 (Dense)              (None, 10)                1290      \n",
      "=================================================================\n",
      "Total params: 44,602\n",
      "Trainable params: 44,602\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = Sequential()\n",
    "model.add(Conv2D(filters=16, kernel_size=2, input_shape=(x_train.shape[1], x_train.shape[2], x_train.shape[3]),\n",
    "                 activation='relu'))\n",
    "model.add(MaxPooling2D(pool_size=2))\n",
    "model.add(Dropout(0.2))\n",
    "\n",
    "model.add(Conv2D(filters=32, kernel_size=2, activation='relu'))\n",
    "model.add(MaxPooling2D(pool_size=2))\n",
    "model.add(Dropout(0.2))\n",
    "\n",
    "model.add(Conv2D(filters=64, kernel_size=2, activation='relu'))\n",
    "model.add(MaxPooling2D(pool_size=2))\n",
    "model.add(Dropout(0.2))\n",
    "\n",
    "model.add(Conv2D(filters=128, kernel_size=2, activation='relu'))\n",
    "model.add(MaxPooling2D(pool_size=2))\n",
    "model.add(Dropout(0.5))\n",
    "model.add(GlobalAveragePooling2D())\n",
    "\n",
    "model.add(Dense(len(encoder.classes_), activation='softmax'))\n",
    "model.summary()\n",
    "\n",
    "adam = keras.optimizers.Adam(learning_rate=0.001)\n",
    "model.compile(loss='categorical_crossentropy', metrics=['accuracy'], optimizer='adam')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 6008 samples, validate on 751 samples\n",
      "Epoch 1/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 4.5328 - accuracy: 0.1265 - val_loss: 2.2263 - val_accuracy: 0.1625\n",
      "Epoch 2/333\n",
      "6008/6008 [==============================] - 23s 4ms/step - loss: 2.2369 - accuracy: 0.1876 - val_loss: 2.0436 - val_accuracy: 0.3196\n",
      "Epoch 3/333\n",
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      "6008/6008 [==============================] - 24s 4ms/step - loss: 0.6749 - accuracy: 0.7878 - val_loss: 0.5193 - val_accuracy: 0.8429\n",
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      "Epoch 47/333\n",
      "6008/6008 [==============================] - 25s 4ms/step - loss: 0.6427 - accuracy: 0.7983 - val_loss: 0.4706 - val_accuracy: 0.8655\n",
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      "Epoch 49/333\n",
      "6008/6008 [==============================] - 27s 4ms/step - loss: 0.6247 - accuracy: 0.7963 - val_loss: 0.4832 - val_accuracy: 0.8575\n",
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      "Epoch 51/333\n",
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      "Epoch 52/333\n",
      "6008/6008 [==============================] - 31s 5ms/step - loss: 0.5891 - accuracy: 0.8076 - val_loss: 0.4695 - val_accuracy: 0.8775\n",
      "Epoch 53/333\n",
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      "6008/6008 [==============================] - 35s 6ms/step - loss: 0.5675 - accuracy: 0.8147 - val_loss: 0.4293 - val_accuracy: 0.8802\n",
      "Epoch 55/333\n",
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      "Epoch 56/333\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "6008/6008 [==============================] - 35s 6ms/step - loss: 0.5454 - accuracy: 0.8207 - val_loss: 0.4612 - val_accuracy: 0.8775\n",
      "Epoch 57/333\n",
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      "Epoch 59/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.5335 - accuracy: 0.8319 - val_loss: 0.4279 - val_accuracy: 0.8748\n",
      "Epoch 60/333\n",
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      "6008/6008 [==============================] - 31s 5ms/step - loss: 0.5156 - accuracy: 0.8336 - val_loss: 0.4214 - val_accuracy: 0.8842\n",
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      "6008/6008 [==============================] - 32s 5ms/step - loss: 0.5134 - accuracy: 0.8319 - val_loss: 0.3928 - val_accuracy: 0.8868\n",
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      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.4408 - accuracy: 0.8614 - val_loss: 0.3613 - val_accuracy: 0.9028\n",
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      "6008/6008 [==============================] - 28s 5ms/step - loss: 0.4423 - accuracy: 0.8540 - val_loss: 0.3582 - val_accuracy: 0.8961\n",
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      "6008/6008 [==============================] - 32s 5ms/step - loss: 0.4151 - accuracy: 0.8667 - val_loss: 0.3521 - val_accuracy: 0.9108\n",
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      "6008/6008 [==============================] - 33s 5ms/step - loss: 0.4100 - accuracy: 0.8650 - val_loss: 0.3319 - val_accuracy: 0.8935\n",
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      "6008/6008 [==============================] - 35s 6ms/step - loss: 0.3997 - accuracy: 0.8633 - val_loss: 0.3486 - val_accuracy: 0.9121\n",
      "Epoch 86/333\n",
      "6008/6008 [==============================] - 32s 5ms/step - loss: 0.4166 - accuracy: 0.8602 - val_loss: 0.3409 - val_accuracy: 0.9068\n",
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      "6008/6008 [==============================] - 31s 5ms/step - loss: 0.4009 - accuracy: 0.8713 - val_loss: 0.3388 - val_accuracy: 0.9015\n",
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      "6008/6008 [==============================] - 34s 6ms/step - loss: 0.3918 - accuracy: 0.8685 - val_loss: 0.3284 - val_accuracy: 0.9041\n",
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      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.3607 - accuracy: 0.8800 - val_loss: 0.3175 - val_accuracy: 0.9161\n",
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     ]
    },
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     "text": [
      "Epoch 112/333\n",
      "6008/6008 [==============================] - 31s 5ms/step - loss: 0.3335 - accuracy: 0.8891 - val_loss: 0.2794 - val_accuracy: 0.9148\n",
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      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.3334 - accuracy: 0.8860 - val_loss: 0.2832 - val_accuracy: 0.9148\n",
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      "Epoch 117/333\n",
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      "Epoch 118/333\n",
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      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.3151 - accuracy: 0.8941 - val_loss: 0.2705 - val_accuracy: 0.9294\n",
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      "Epoch 121/333\n",
      "6008/6008 [==============================] - 31s 5ms/step - loss: 0.3121 - accuracy: 0.8936 - val_loss: 0.2640 - val_accuracy: 0.9214\n",
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      "Epoch 167/333\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.2573 - accuracy: 0.9106 - val_loss: 0.2582 - val_accuracy: 0.9254\n",
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      "Epoch 222/333\n"
     ]
    },
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     "text": [
      "6008/6008 [==============================] - 31s 5ms/step - loss: 0.2024 - accuracy: 0.9341 - val_loss: 0.2541 - val_accuracy: 0.9294\n",
      "Epoch 223/333\n",
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      "Epoch 241/333\n",
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      "6008/6008 [==============================] - 28s 5ms/step - loss: 0.1999 - accuracy: 0.9313 - val_loss: 0.2566 - val_accuracy: 0.9254\n",
      "Epoch 243/333\n",
      "6008/6008 [==============================] - 28s 5ms/step - loss: 0.1894 - accuracy: 0.9376 - val_loss: 0.2282 - val_accuracy: 0.9361\n",
      "Epoch 244/333\n",
      "6008/6008 [==============================] - 28s 5ms/step - loss: 0.1834 - accuracy: 0.9402 - val_loss: 0.2478 - val_accuracy: 0.9374\n",
      "Epoch 245/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1965 - accuracy: 0.9324 - val_loss: 0.2504 - val_accuracy: 0.9294\n",
      "Epoch 246/333\n",
      "6008/6008 [==============================] - 32s 5ms/step - loss: 0.1962 - accuracy: 0.9336 - val_loss: 0.2554 - val_accuracy: 0.9348\n",
      "Epoch 247/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1888 - accuracy: 0.9354 - val_loss: 0.2409 - val_accuracy: 0.9321\n",
      "Epoch 248/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1809 - accuracy: 0.9391 - val_loss: 0.2478 - val_accuracy: 0.9361\n",
      "Epoch 249/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1863 - accuracy: 0.9341 - val_loss: 0.2426 - val_accuracy: 0.9348\n",
      "Epoch 250/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1715 - accuracy: 0.9364 - val_loss: 0.2402 - val_accuracy: 0.9334\n",
      "Epoch 251/333\n",
      "6008/6008 [==============================] - 31s 5ms/step - loss: 0.1997 - accuracy: 0.9311 - val_loss: 0.2532 - val_accuracy: 0.9268\n",
      "Epoch 252/333\n",
      "6008/6008 [==============================] - 31s 5ms/step - loss: 0.2062 - accuracy: 0.9293 - val_loss: 0.2403 - val_accuracy: 0.9294\n",
      "Epoch 253/333\n",
      "6008/6008 [==============================] - 31s 5ms/step - loss: 0.1733 - accuracy: 0.9366 - val_loss: 0.2580 - val_accuracy: 0.9334\n",
      "Epoch 254/333\n",
      "6008/6008 [==============================] - 34s 6ms/step - loss: 0.1985 - accuracy: 0.9356 - val_loss: 0.2726 - val_accuracy: 0.9308\n",
      "Epoch 255/333\n",
      "6008/6008 [==============================] - 31s 5ms/step - loss: 0.1974 - accuracy: 0.9356 - val_loss: 0.2356 - val_accuracy: 0.9387\n",
      "Epoch 256/333\n",
      "6008/6008 [==============================] - 31s 5ms/step - loss: 0.1924 - accuracy: 0.9333 - val_loss: 0.2273 - val_accuracy: 0.9441\n",
      "Epoch 257/333\n",
      "6008/6008 [==============================] - 40s 7ms/step - loss: 0.1870 - accuracy: 0.9364 - val_loss: 0.2408 - val_accuracy: 0.9361\n",
      "Epoch 258/333\n",
      "6008/6008 [==============================] - 34s 6ms/step - loss: 0.1821 - accuracy: 0.9384 - val_loss: 0.2436 - val_accuracy: 0.9414\n",
      "Epoch 259/333\n",
      "6008/6008 [==============================] - 27s 4ms/step - loss: 0.1825 - accuracy: 0.9397 - val_loss: 0.2610 - val_accuracy: 0.9268\n",
      "Epoch 260/333\n",
      "6008/6008 [==============================] - 38s 6ms/step - loss: 0.1772 - accuracy: 0.9384 - val_loss: 0.2424 - val_accuracy: 0.9361\n",
      "Epoch 261/333\n",
      "6008/6008 [==============================] - 37s 6ms/step - loss: 0.1885 - accuracy: 0.9351 - val_loss: 0.2510 - val_accuracy: 0.9268\n",
      "Epoch 262/333\n",
      "6008/6008 [==============================] - 31s 5ms/step - loss: 0.1715 - accuracy: 0.9404 - val_loss: 0.2511 - val_accuracy: 0.9281\n",
      "Epoch 263/333\n",
      "6008/6008 [==============================] - 34s 6ms/step - loss: 0.1877 - accuracy: 0.9331 - val_loss: 0.2301 - val_accuracy: 0.9334\n",
      "Epoch 264/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1862 - accuracy: 0.9364 - val_loss: 0.2497 - val_accuracy: 0.9334\n",
      "Epoch 265/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1980 - accuracy: 0.9369 - val_loss: 0.2608 - val_accuracy: 0.9294\n",
      "Epoch 266/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1805 - accuracy: 0.9351 - val_loss: 0.2355 - val_accuracy: 0.9308\n",
      "Epoch 267/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1725 - accuracy: 0.9406 - val_loss: 0.2539 - val_accuracy: 0.9268\n",
      "Epoch 268/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1743 - accuracy: 0.9412 - val_loss: 0.2578 - val_accuracy: 0.9268\n",
      "Epoch 269/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1755 - accuracy: 0.9379 - val_loss: 0.2645 - val_accuracy: 0.9254\n",
      "Epoch 270/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1874 - accuracy: 0.9369 - val_loss: 0.2360 - val_accuracy: 0.9308\n",
      "Epoch 271/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1832 - accuracy: 0.9353 - val_loss: 0.2240 - val_accuracy: 0.9308\n",
      "Epoch 272/333\n",
      "6008/6008 [==============================] - 28s 5ms/step - loss: 0.1762 - accuracy: 0.9381 - val_loss: 0.2247 - val_accuracy: 0.9348\n",
      "Epoch 273/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1919 - accuracy: 0.9369 - val_loss: 0.2403 - val_accuracy: 0.9401\n",
      "Epoch 274/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1871 - accuracy: 0.9366 - val_loss: 0.2505 - val_accuracy: 0.9361\n",
      "Epoch 275/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1859 - accuracy: 0.9354 - val_loss: 0.2209 - val_accuracy: 0.9348\n",
      "Epoch 276/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1886 - accuracy: 0.9356 - val_loss: 0.2314 - val_accuracy: 0.9401\n",
      "Epoch 277/333\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1766 - accuracy: 0.9417 - val_loss: 0.2491 - val_accuracy: 0.9294\n",
      "Epoch 278/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1817 - accuracy: 0.9389 - val_loss: 0.2390 - val_accuracy: 0.9348\n",
      "Epoch 279/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1787 - accuracy: 0.9396 - val_loss: 0.2268 - val_accuracy: 0.9454\n",
      "Epoch 280/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1800 - accuracy: 0.9399 - val_loss: 0.2424 - val_accuracy: 0.9374\n",
      "Epoch 281/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1814 - accuracy: 0.9371 - val_loss: 0.2552 - val_accuracy: 0.9308\n",
      "Epoch 282/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1849 - accuracy: 0.9361 - val_loss: 0.2275 - val_accuracy: 0.9414\n",
      "Epoch 283/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1719 - accuracy: 0.9421 - val_loss: 0.2150 - val_accuracy: 0.9427\n",
      "Epoch 284/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1741 - accuracy: 0.9419 - val_loss: 0.2267 - val_accuracy: 0.9321\n",
      "Epoch 285/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1823 - accuracy: 0.9353 - val_loss: 0.2321 - val_accuracy: 0.9387\n",
      "Epoch 286/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1802 - accuracy: 0.9379 - val_loss: 0.2287 - val_accuracy: 0.9401\n",
      "Epoch 287/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1688 - accuracy: 0.9481 - val_loss: 0.2470 - val_accuracy: 0.9334\n",
      "Epoch 288/333\n",
      "6008/6008 [==============================] - 27s 4ms/step - loss: 0.1724 - accuracy: 0.9397 - val_loss: 0.2459 - val_accuracy: 0.9294\n",
      "Epoch 289/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1877 - accuracy: 0.9386 - val_loss: 0.2306 - val_accuracy: 0.9348\n",
      "Epoch 290/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1693 - accuracy: 0.9412 - val_loss: 0.2531 - val_accuracy: 0.9308\n",
      "Epoch 291/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1869 - accuracy: 0.9354 - val_loss: 0.2282 - val_accuracy: 0.9361\n",
      "Epoch 292/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1760 - accuracy: 0.9386 - val_loss: 0.2372 - val_accuracy: 0.9334\n",
      "Epoch 293/333\n",
      "6008/6008 [==============================] - 31s 5ms/step - loss: 0.1570 - accuracy: 0.9499 - val_loss: 0.2416 - val_accuracy: 0.9334\n",
      "Epoch 294/333\n",
      "6008/6008 [==============================] - 28s 5ms/step - loss: 0.1733 - accuracy: 0.9384 - val_loss: 0.2397 - val_accuracy: 0.9374\n",
      "Epoch 295/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1731 - accuracy: 0.9402 - val_loss: 0.2544 - val_accuracy: 0.9308\n",
      "Epoch 296/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1849 - accuracy: 0.9366 - val_loss: 0.2317 - val_accuracy: 0.9401\n",
      "Epoch 297/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1597 - accuracy: 0.9481 - val_loss: 0.2465 - val_accuracy: 0.9334\n",
      "Epoch 298/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1711 - accuracy: 0.9414 - val_loss: 0.2474 - val_accuracy: 0.9254\n",
      "Epoch 299/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1650 - accuracy: 0.9442 - val_loss: 0.2512 - val_accuracy: 0.9308\n",
      "Epoch 300/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1815 - accuracy: 0.9384 - val_loss: 0.2298 - val_accuracy: 0.9387\n",
      "Epoch 301/333\n",
      "6008/6008 [==============================] - 29s 5ms/step - loss: 0.1684 - accuracy: 0.9392 - val_loss: 0.2298 - val_accuracy: 0.9387\n",
      "Epoch 302/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1687 - accuracy: 0.9382 - val_loss: 0.2312 - val_accuracy: 0.9334\n",
      "Epoch 303/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1881 - accuracy: 0.9336 - val_loss: 0.2294 - val_accuracy: 0.9361\n",
      "Epoch 304/333\n",
      "6008/6008 [==============================] - 31s 5ms/step - loss: 0.1757 - accuracy: 0.9431 - val_loss: 0.2302 - val_accuracy: 0.9321\n",
      "Epoch 305/333\n",
      "6008/6008 [==============================] - 32s 5ms/step - loss: 0.1621 - accuracy: 0.9472 - val_loss: 0.2343 - val_accuracy: 0.9321\n",
      "Epoch 306/333\n",
      "6008/6008 [==============================] - 32s 5ms/step - loss: 0.1673 - accuracy: 0.9446 - val_loss: 0.2345 - val_accuracy: 0.9321\n",
      "Epoch 307/333\n",
      "6008/6008 [==============================] - 32s 5ms/step - loss: 0.1516 - accuracy: 0.9486 - val_loss: 0.2330 - val_accuracy: 0.9294\n",
      "Epoch 308/333\n",
      "6008/6008 [==============================] - 31s 5ms/step - loss: 0.1790 - accuracy: 0.9387 - val_loss: 0.2393 - val_accuracy: 0.9334\n",
      "Epoch 309/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1633 - accuracy: 0.9432 - val_loss: 0.2460 - val_accuracy: 0.9348\n",
      "Epoch 310/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1690 - accuracy: 0.9412 - val_loss: 0.2461 - val_accuracy: 0.9334\n",
      "Epoch 311/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1850 - accuracy: 0.9377 - val_loss: 0.2186 - val_accuracy: 0.9401\n",
      "Epoch 312/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1633 - accuracy: 0.9411 - val_loss: 0.2340 - val_accuracy: 0.9348\n",
      "Epoch 313/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1788 - accuracy: 0.9404 - val_loss: 0.2329 - val_accuracy: 0.9374\n",
      "Epoch 314/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1612 - accuracy: 0.9459 - val_loss: 0.2517 - val_accuracy: 0.9294\n",
      "Epoch 315/333\n",
      "6008/6008 [==============================] - 30s 5ms/step - loss: 0.1726 - accuracy: 0.9406 - val_loss: 0.2524 - val_accuracy: 0.9308\n",
      "Epoch 316/333\n",
      "6008/6008 [==============================] - 24s 4ms/step - loss: 0.1613 - accuracy: 0.9469 - val_loss: 0.2411 - val_accuracy: 0.9281\n",
      "Epoch 317/333\n",
      "6008/6008 [==============================] - 20s 3ms/step - loss: 0.1714 - accuracy: 0.9424 - val_loss: 0.2206 - val_accuracy: 0.9414\n",
      "Epoch 318/333\n",
      "6008/6008 [==============================] - 22s 4ms/step - loss: 0.1682 - accuracy: 0.9414 - val_loss: 0.2286 - val_accuracy: 0.9374\n",
      "Epoch 319/333\n",
      "6008/6008 [==============================] - 22s 4ms/step - loss: 0.1599 - accuracy: 0.9447 - val_loss: 0.2160 - val_accuracy: 0.9427\n",
      "Epoch 320/333\n",
      "6008/6008 [==============================] - 21s 3ms/step - loss: 0.1658 - accuracy: 0.9419 - val_loss: 0.2303 - val_accuracy: 0.9361\n",
      "Epoch 321/333\n",
      "6008/6008 [==============================] - 26s 4ms/step - loss: 0.1624 - accuracy: 0.9436 - val_loss: 0.2349 - val_accuracy: 0.9321\n",
      "Epoch 322/333\n",
      "6008/6008 [==============================] - 23s 4ms/step - loss: 0.1704 - accuracy: 0.9394 - val_loss: 0.2249 - val_accuracy: 0.9427\n",
      "Epoch 323/333\n",
      "6008/6008 [==============================] - 22s 4ms/step - loss: 0.1664 - accuracy: 0.9437 - val_loss: 0.2478 - val_accuracy: 0.9281\n",
      "Epoch 324/333\n",
      "6008/6008 [==============================] - 23s 4ms/step - loss: 0.1735 - accuracy: 0.9399 - val_loss: 0.2161 - val_accuracy: 0.9374\n",
      "Epoch 325/333\n",
      "6008/6008 [==============================] - 22s 4ms/step - loss: 0.1734 - accuracy: 0.9416 - val_loss: 0.2192 - val_accuracy: 0.9414\n",
      "Epoch 326/333\n",
      "6008/6008 [==============================] - 22s 4ms/step - loss: 0.1705 - accuracy: 0.9412 - val_loss: 0.2217 - val_accuracy: 0.9387\n",
      "Epoch 327/333\n",
      "6008/6008 [==============================] - 23s 4ms/step - loss: 0.1697 - accuracy: 0.9429 - val_loss: 0.2343 - val_accuracy: 0.9374\n",
      "Epoch 328/333\n",
      "6008/6008 [==============================] - 25s 4ms/step - loss: 0.1706 - accuracy: 0.9444 - val_loss: 0.2097 - val_accuracy: 0.9414\n",
      "Epoch 329/333\n",
      "6008/6008 [==============================] - 23s 4ms/step - loss: 0.1617 - accuracy: 0.9452 - val_loss: 0.2229 - val_accuracy: 0.9348\n",
      "Epoch 330/333\n",
      "6008/6008 [==============================] - 22s 4ms/step - loss: 0.1762 - accuracy: 0.9394 - val_loss: 0.2228 - val_accuracy: 0.9361\n",
      "Epoch 331/333\n",
      "6008/6008 [==============================] - 23s 4ms/step - loss: 0.1586 - accuracy: 0.9469 - val_loss: 0.2423 - val_accuracy: 0.9361\n",
      "Epoch 332/333\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6008/6008 [==============================] - 22s 4ms/step - loss: 0.1589 - accuracy: 0.9464 - val_loss: 0.2556 - val_accuracy: 0.9321\n",
      "Epoch 333/333\n",
      "6008/6008 [==============================] - 22s 4ms/step - loss: 0.1532 - accuracy: 0.9471 - val_loss: 0.2309 - val_accuracy: 0.9308\n"
     ]
    }
   ],
   "source": [
    "history = model.fit(x_train, y_train,\n",
    "                    batch_size=128,\n",
    "                    epochs=333,\n",
    "                    validation_data=(x_val, y_val),\n",
    "                    class_weight=class_weights,\n",
    "                    shuffle=True)\n",
    "\n",
    "\n",
    "model_name = \"language_classifier-4s-better-val.h5\"\n",
    "model.save(model_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "751/751 [==============================] - 1s 1ms/step\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      finish       0.95      0.98      0.96        81\n",
      "    georgian       0.95      0.82      0.88        74\n",
      "       greek       0.96      0.96      0.96        78\n",
      "   hungarian       0.94      1.00      0.97        72\n",
      "    japanese       0.89      0.92      0.91        64\n",
      "     ltalian       0.96      0.94      0.95        81\n",
      "   slovenian       0.90      0.99      0.94        75\n",
      "     swedish       0.93      0.82      0.87        78\n",
      "        thai       0.95      0.92      0.94        79\n",
      "  viatnamese       0.86      0.94      0.90        69\n",
      "\n",
      "    accuracy                           0.93       751\n",
      "   macro avg       0.93      0.93      0.93       751\n",
      "weighted avg       0.93      0.93      0.93       751\n",
      "\n"
     ]
    }
   ],
   "source": [
    "predictions = model.predict(x_test, verbose=1)\n",
    "\n",
    "y_true, y_pred = [],[]\n",
    "classes = encoder.classes_\n",
    "for idx, prediction in enumerate(predictions): \n",
    "    y_true.append(classes[np.argmax(y_test[idx])])\n",
    "    y_pred.append(classes[np.argmax(prediction)])\n",
    "    \n",
    "print(classification_report(y_pred, y_true))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}