From f86e23896c7767ed940bbf207e9e164c17054aef Mon Sep 17 00:00:00 2001
From: Mirko Birbaumer <mirko.birbaumer@hslu.ch>
Date: Thu, 28 Oct 2021 04:53:04 +0000
Subject: [PATCH] Replaced model.predict_classes by
 np.argmax(model.predict(...), axis=-1)

---
 ...k Block 6 - RNN and Image Captioning.ipynb | 946 +++++++++---------
 1 file changed, 459 insertions(+), 487 deletions(-)

diff --git a/notebooks/Block_6/Jupyter Notebook Block 6 - RNN and Image Captioning.ipynb b/notebooks/Block_6/Jupyter Notebook Block 6 - RNN and Image Captioning.ipynb
index 3d7051f..49b0588 100644
--- a/notebooks/Block_6/Jupyter Notebook Block 6 - RNN and Image Captioning.ipynb	
+++ b/notebooks/Block_6/Jupyter Notebook Block 6 - RNN and Image Captioning.ipynb	
@@ -20,13 +20,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Downloading data from http://www.gutenberg.org/files/21000/21000-8.txt\n",
+      "229376/227569 [==============================] - 0s 1us/step\n",
       " mögt ihr walten,\n",
       "Wie ihr aus Dunst und Nebel um mich steigt;\n",
       "Mein Busen fühlt sich jugendlich erschüttert\n",
@@ -99,7 +101,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -128,7 +130,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -177,7 +179,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -227,7 +229,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -248,7 +250,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -301,7 +303,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -351,7 +353,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -373,7 +375,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -409,7 +411,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -454,7 +456,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -503,7 +505,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -525,26 +527,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Model: \"sequential_1\"\n",
+      "Model: \"sequential\"\n",
       "_________________________________________________________________\n",
       "Layer (type)                 Output Shape              Param #   \n",
       "=================================================================\n",
-      "embedding_1 (Embedding)      (None, 50, 50)            350300    \n",
+      "embedding (Embedding)        (None, 50, 50)            350300    \n",
       "_________________________________________________________________\n",
-      "lstm_2 (LSTM)                (None, 50, 100)           60400     \n",
+      "lstm (LSTM)                  (None, 50, 100)           60400     \n",
       "_________________________________________________________________\n",
-      "lstm_3 (LSTM)                (None, 100)               80400     \n",
+      "lstm_1 (LSTM)                (None, 100)               80400     \n",
       "_________________________________________________________________\n",
-      "dense_2 (Dense)              (None, 100)               10100     \n",
+      "dense (Dense)                (None, 100)               10100     \n",
       "_________________________________________________________________\n",
-      "dense_3 (Dense)              (None, 7006)              707606    \n",
+      "dense_1 (Dense)              (None, 7006)              707606    \n",
       "=================================================================\n",
       "Total params: 1,208,806\n",
       "Trainable params: 1,208,806\n",
@@ -571,811 +573,768 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Train on 33549 samples\n",
       "Epoch 1/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 7.6015 - accuracy: 0.0256WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 64s 440ms/step - loss: 7.9855 - accuracy: 0.0194\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 53s 2ms/sample - loss: 7.6019 - accuracy: 0.0256\n",
       "Epoch 2/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 7.1517 - accuracy: 0.0273WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 59s 446ms/step - loss: 7.1538 - accuracy: 0.0270\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 46s 1ms/sample - loss: 7.1512 - accuracy: 0.0273\n",
       "Epoch 3/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 7.0093 - accuracy: 0.0265WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 61s 461ms/step - loss: 7.0045 - accuracy: 0.0270\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 7.0095 - accuracy: 0.0265\n",
       "Epoch 4/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 6.8323 - accuracy: 0.0302WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 60s 457ms/step - loss: 6.9123 - accuracy: 0.0285\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 46s 1ms/sample - loss: 6.8321 - accuracy: 0.0302\n",
       "Epoch 5/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 6.6149 - accuracy: 0.0361WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 61s 460ms/step - loss: 6.8054 - accuracy: 0.0290\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 46s 1ms/sample - loss: 6.6146 - accuracy: 0.0361\n",
       "Epoch 6/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 6.4739 - accuracy: 0.0386WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 61s 458ms/step - loss: 6.6642 - accuracy: 0.0328\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 46s 1ms/sample - loss: 6.4739 - accuracy: 0.0386\n",
       "Epoch 7/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 6.3614 - accuracy: 0.0415WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 59s 447ms/step - loss: 6.4980 - accuracy: 0.0401\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 6.3614 - accuracy: 0.0416\n",
       "Epoch 8/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 6.2550 - accuracy: 0.0440WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 58s 436ms/step - loss: 6.3643 - accuracy: 0.0425\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 6.2547 - accuracy: 0.0439\n",
       "Epoch 9/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 6.1668 - accuracy: 0.0447WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 59s 444ms/step - loss: 6.2553 - accuracy: 0.0441\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 6.1670 - accuracy: 0.0447\n",
       "Epoch 10/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 6.0883 - accuracy: 0.0478WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 436ms/step - loss: 6.1756 - accuracy: 0.0475\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 6.0882 - accuracy: 0.0478\n",
       "Epoch 11/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 6.0216 - accuracy: 0.0502WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 59s 445ms/step - loss: 6.1012 - accuracy: 0.0507\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 46s 1ms/sample - loss: 6.0221 - accuracy: 0.0502\n",
       "Epoch 12/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 5.9525 - accuracy: 0.0515WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 434ms/step - loss: 6.0541 - accuracy: 0.0487\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 5.9524 - accuracy: 0.0515\n",
       "Epoch 13/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 5.8864 - accuracy: 0.0522WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 60s 453ms/step - loss: 5.9791 - accuracy: 0.0520\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 5.8869 - accuracy: 0.0522\n",
       "Epoch 14/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 5.8199 - accuracy: 0.0543WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 59s 445ms/step - loss: 5.8897 - accuracy: 0.0513\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 49s 1ms/sample - loss: 5.8197 - accuracy: 0.0544\n",
-      "Epoch 15/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 5.7495 - accuracy: 0.0550WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 5.7498 - accuracy: 0.0550\n",
       "Epoch 16/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 5.6753 - accuracy: 0.0578WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 60s 452ms/step - loss: 5.8274 - accuracy: 0.0562\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 5.6755 - accuracy: 0.0578\n",
       "Epoch 17/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 5.5986 - accuracy: 0.0590WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 61s 462ms/step - loss: 5.7648 - accuracy: 0.0572\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 49s 1ms/sample - loss: 5.5989 - accuracy: 0.0590\n",
       "Epoch 18/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 5.5267 - accuracy: 0.0613WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 62s 468ms/step - loss: 5.7030 - accuracy: 0.0600\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 5.5264 - accuracy: 0.0613\n",
       "Epoch 19/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 5.4496 - accuracy: 0.0628WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 60s 458ms/step - loss: 5.6397 - accuracy: 0.0601\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 5.4498 - accuracy: 0.0628\n",
       "Epoch 20/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 5.3814 - accuracy: 0.0650WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 59s 447ms/step - loss: 5.5928 - accuracy: 0.0617\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 5.3812 - accuracy: 0.0650\n",
       "Epoch 21/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 5.3068 - accuracy: 0.0672WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 59s 449ms/step - loss: 5.5524 - accuracy: 0.0609\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 49s 1ms/sample - loss: 5.3069 - accuracy: 0.0672\n",
       "Epoch 22/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 5.2312 - accuracy: 0.0700WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 58s 437ms/step - loss: 5.4603 - accuracy: 0.0651\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 49s 1ms/sample - loss: 5.2310 - accuracy: 0.0700\n",
       "Epoch 23/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 5.1572 - accuracy: 0.0718WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 59s 445ms/step - loss: 5.4244 - accuracy: 0.0655\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 5.1572 - accuracy: 0.0718\n",
       "Epoch 24/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 5.0897 - accuracy: 0.0745WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 58s 437ms/step - loss: 5.3747 - accuracy: 0.0681\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 49s 1ms/sample - loss: 5.0898 - accuracy: 0.0745\n",
       "Epoch 25/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 5.0156 - accuracy: 0.0769WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 59s 443ms/step - loss: 5.3031 - accuracy: 0.0699\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 5.0158 - accuracy: 0.0769\n",
       "Epoch 26/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 4.9431 - accuracy: 0.0803WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 434ms/step - loss: 5.2824 - accuracy: 0.0723\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 4.9432 - accuracy: 0.0802\n",
       "Epoch 27/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 4.8671 - accuracy: 0.0843WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 435ms/step - loss: 5.2316 - accuracy: 0.0739\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 4.8673 - accuracy: 0.0843\n",
       "Epoch 28/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 4.7983 - accuracy: 0.0873WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 432ms/step - loss: 5.1599 - accuracy: 0.0763\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 4.7986 - accuracy: 0.0873\n",
       "Epoch 29/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 4.7307 - accuracy: 0.0912WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 58s 443ms/step - loss: 5.1399 - accuracy: 0.0767\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 4.7307 - accuracy: 0.0912\n",
       "Epoch 30/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 4.6548 - accuracy: 0.0961WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 426ms/step - loss: 5.0655 - accuracy: 0.0792\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 4.6546 - accuracy: 0.0962\n",
       "Epoch 31/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 4.5846 - accuracy: 0.1013WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 433ms/step - loss: 5.0166 - accuracy: 0.0806\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 4.5846 - accuracy: 0.1013\n",
       "Epoch 32/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 4.5059 - accuracy: 0.1088WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 429ms/step - loss: 4.9646 - accuracy: 0.0823\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 4.5060 - accuracy: 0.1088\n",
       "Epoch 33/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 4.4415 - accuracy: 0.1146WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 432ms/step - loss: 4.9360 - accuracy: 0.0836\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 4.4416 - accuracy: 0.1146\n",
       "Epoch 34/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 4.3711 - accuracy: 0.1222WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 429ms/step - loss: 4.8735 - accuracy: 0.0861\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 4.3711 - accuracy: 0.1222\n",
       "Epoch 35/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 4.3028 - accuracy: 0.1302WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 426ms/step - loss: 4.7967 - accuracy: 0.0919\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 4.3029 - accuracy: 0.1302\n",
       "Epoch 36/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 4.2402 - accuracy: 0.1380WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 430ms/step - loss: 4.7571 - accuracy: 0.0905\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 4.2402 - accuracy: 0.1379\n",
       "Epoch 37/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 4.1797 - accuracy: 0.1457WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 4.1796 - accuracy: 0.1457\n",
-      "Epoch 38/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 4.1106 - accuracy: 0.1569WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 4.1106 - accuracy: 0.1570\n",
-      "Epoch 39/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 4.0483 - accuracy: 0.1647WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 4.0485 - accuracy: 0.1647\n",
-      "Epoch 40/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.9894 - accuracy: 0.1724WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 3.9895 - accuracy: 0.1724\n",
-      "Epoch 41/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.9309 - accuracy: 0.1811WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 3.9309 - accuracy: 0.1811\n",
-      "Epoch 42/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.8759 - accuracy: 0.1899WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 3.8759 - accuracy: 0.1899\n",
-      "Epoch 43/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.8169 - accuracy: 0.1981WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 3.8172 - accuracy: 0.1980\n",
-      "Epoch 44/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.7583 - accuracy: 0.2088WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 3.7582 - accuracy: 0.2088\n",
-      "Epoch 45/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.7058 - accuracy: 0.2167WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 3.7060 - accuracy: 0.2167\n",
-      "Epoch 46/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.6524 - accuracy: 0.2301WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 3.6523 - accuracy: 0.2301\n",
-      "Epoch 47/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.6044 - accuracy: 0.2360WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      " 47/132 [=========>....................] - ETA: 36s - loss: 4.6476 - accuracy: 0.1033"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "IOPub message rate exceeded.\n",
+      "The notebook server will temporarily stop sending output\n",
+      "to the client in order to avoid crashing it.\n",
+      "To change this limit, set the config variable\n",
+      "`--NotebookApp.iopub_msg_rate_limit`.\n",
+      "\n",
+      "Current values:\n",
+      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
+      "NotebookApp.rate_limit_window=3.0 (secs)\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "132/132 [==============================] - 58s 442ms/step - loss: 4.2386 - accuracy: 0.1423\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 3.6045 - accuracy: 0.2360\n",
       "Epoch 48/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.5476 - accuracy: 0.2443WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 61s 459ms/step - loss: 4.1897 - accuracy: 0.1459\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 3.5478 - accuracy: 0.2443\n",
       "Epoch 49/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.5011 - accuracy: 0.2523WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 59s 450ms/step - loss: 4.1521 - accuracy: 0.1502\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 3.5014 - accuracy: 0.2523\n",
       "Epoch 50/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.4601 - accuracy: 0.2603WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 59s 448ms/step - loss: 4.1048 - accuracy: 0.1577\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 3.4600 - accuracy: 0.2602\n",
       "Epoch 51/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.4058 - accuracy: 0.2702WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 58s 440ms/step - loss: 4.0382 - accuracy: 0.1673\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 3.4059 - accuracy: 0.2702\n",
       "Epoch 52/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.3570 - accuracy: 0.2793WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 58s 437ms/step - loss: 4.0287 - accuracy: 0.1699\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 3.3572 - accuracy: 0.2793\n",
       "Epoch 53/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.3133 - accuracy: 0.2850WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 429ms/step - loss: 3.9748 - accuracy: 0.1792\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 3.3131 - accuracy: 0.2850\n",
       "Epoch 54/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.2754 - accuracy: 0.2924WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 58s 438ms/step - loss: 3.9144 - accuracy: 0.1873\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 3.2753 - accuracy: 0.2924\n",
       "Epoch 55/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.2363 - accuracy: 0.3007WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 58s 440ms/step - loss: 3.8847 - accuracy: 0.1897\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 3.2361 - accuracy: 0.3008\n",
       "Epoch 56/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.1929 - accuracy: 0.3083WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 428ms/step - loss: 3.8189 - accuracy: 0.2030\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 3.1927 - accuracy: 0.3084\n",
       "Epoch 57/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.1515 - accuracy: 0.3143WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 58s 436ms/step - loss: 3.7989 - accuracy: 0.2032\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 3.1519 - accuracy: 0.3143\n",
       "Epoch 58/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.1186 - accuracy: 0.3206WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 428ms/step - loss: 3.7453 - accuracy: 0.2166\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 3.1188 - accuracy: 0.3206\n",
       "Epoch 59/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.0711 - accuracy: 0.3320WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 434ms/step - loss: 3.7133 - accuracy: 0.2185\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 3.0712 - accuracy: 0.3320\n",
       "Epoch 60/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.0397 - accuracy: 0.3364WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 430ms/step - loss: 3.6729 - accuracy: 0.2221\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 3.0399 - accuracy: 0.3364\n",
       "Epoch 61/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 3.0060 - accuracy: 0.3419WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 435ms/step - loss: 3.6343 - accuracy: 0.2336\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 3.0060 - accuracy: 0.3419\n",
       "Epoch 62/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.9942 - accuracy: 0.3403WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 419ms/step - loss: 3.5992 - accuracy: 0.2358\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 2.9945 - accuracy: 0.3402\n",
       "Epoch 63/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.9397 - accuracy: 0.3525WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 425ms/step - loss: 3.5368 - accuracy: 0.2526\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.9392 - accuracy: 0.3526\n",
       "Epoch 64/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.8967 - accuracy: 0.3592WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 434ms/step - loss: 3.5339 - accuracy: 0.2474\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.8966 - accuracy: 0.3592\n",
       "Epoch 65/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.8706 - accuracy: 0.3664WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 424ms/step - loss: 3.4862 - accuracy: 0.2583\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.8707 - accuracy: 0.3663\n",
       "Epoch 66/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.8385 - accuracy: 0.3706WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 434ms/step - loss: 3.4550 - accuracy: 0.2640\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.8387 - accuracy: 0.3705\n",
       "Epoch 67/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.8082 - accuracy: 0.3757WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 434ms/step - loss: 3.4344 - accuracy: 0.2657\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.8081 - accuracy: 0.3757\n",
       "Epoch 68/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.7849 - accuracy: 0.3771WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 426ms/step - loss: 3.3755 - accuracy: 0.2787\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.7850 - accuracy: 0.3771\n",
       "Epoch 69/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.7496 - accuracy: 0.3854WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.7495 - accuracy: 0.3854\n",
-      "Epoch 70/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.7183 - accuracy: 0.3910WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.7185 - accuracy: 0.3910\n",
-      "Epoch 71/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.6926 - accuracy: 0.3980WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      " 50/132 [==========>...................] - ETA: 36s - loss: 3.3131 - accuracy: 0.2888"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "IOPub message rate exceeded.\n",
+      "The notebook server will temporarily stop sending output\n",
+      "to the client in order to avoid crashing it.\n",
+      "To change this limit, set the config variable\n",
+      "`--NotebookApp.iopub_msg_rate_limit`.\n",
+      "\n",
+      "Current values:\n",
+      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
+      "NotebookApp.rate_limit_window=3.0 (secs)\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "132/132 [==============================] - 59s 450ms/step - loss: 3.2895 - accuracy: 0.2973\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.6927 - accuracy: 0.3980\n",
       "Epoch 72/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.6641 - accuracy: 0.4029WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 58s 438ms/step - loss: 3.2864 - accuracy: 0.2902\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.6643 - accuracy: 0.4028\n",
       "Epoch 73/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.6417 - accuracy: 0.4046WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 58s 441ms/step - loss: 3.2354 - accuracy: 0.2987\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 2.6418 - accuracy: 0.4046\n",
       "Epoch 74/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.6221 - accuracy: 0.4098WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 428ms/step - loss: 3.2250 - accuracy: 0.3055\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 2.6222 - accuracy: 0.4098\n",
       "Epoch 75/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.5986 - accuracy: 0.4140WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 435ms/step - loss: 3.1862 - accuracy: 0.3107\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 2.5987 - accuracy: 0.4141\n",
       "Epoch 76/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.5569 - accuracy: 0.4222WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 59s 446ms/step - loss: 3.1453 - accuracy: 0.3172\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.5570 - accuracy: 0.4221\n",
       "Epoch 77/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.5347 - accuracy: 0.4278WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 434ms/step - loss: 3.1511 - accuracy: 0.3115\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.5349 - accuracy: 0.4278\n",
       "Epoch 78/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.5190 - accuracy: 0.4299WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 427ms/step - loss: 3.1045 - accuracy: 0.3246\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.5192 - accuracy: 0.4299\n",
       "Epoch 79/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.5160 - accuracy: 0.4271WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 62s 469ms/step - loss: 3.0800 - accuracy: 0.3291\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.5157 - accuracy: 0.4272\n",
       "Epoch 80/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.4712 - accuracy: 0.4372WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 60s 453ms/step - loss: 3.0535 - accuracy: 0.3289\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.4711 - accuracy: 0.4372\n",
       "Epoch 81/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.4473 - accuracy: 0.4414WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 59s 449ms/step - loss: 3.0297 - accuracy: 0.3402\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 46s 1ms/sample - loss: 2.4472 - accuracy: 0.4414\n",
       "Epoch 82/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.4155 - accuracy: 0.4514WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 58s 438ms/step - loss: 3.0165 - accuracy: 0.3408\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.4154 - accuracy: 0.4515\n",
       "Epoch 83/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.3977 - accuracy: 0.4535WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 425ms/step - loss: 2.9586 - accuracy: 0.3578\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.3975 - accuracy: 0.4535\n",
       "Epoch 84/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.3798 - accuracy: 0.4548WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 426ms/step - loss: 2.9457 - accuracy: 0.3546\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.3797 - accuracy: 0.4549\n",
       "Epoch 85/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.3571 - accuracy: 0.4598WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 430ms/step - loss: 2.9160 - accuracy: 0.3564\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.3570 - accuracy: 0.4598\n",
       "Epoch 86/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.3404 - accuracy: 0.4629WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 58s 436ms/step - loss: 2.8669 - accuracy: 0.3670\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 2.3407 - accuracy: 0.4628\n",
-      "Epoch 87/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.3224 - accuracy: 0.4678WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.3225 - accuracy: 0.4678\n",
-      "Epoch 88/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.3009 - accuracy: 0.4702WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.3010 - accuracy: 0.4701\n",
       "Epoch 89/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.2780 - accuracy: 0.4740WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 431ms/step - loss: 2.8534 - accuracy: 0.3723\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.2782 - accuracy: 0.4739\n",
       "Epoch 90/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.2663 - accuracy: 0.4786WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 425ms/step - loss: 2.7904 - accuracy: 0.3844\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.2663 - accuracy: 0.4786\n",
       "Epoch 91/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.2450 - accuracy: 0.4796WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 430ms/step - loss: 2.7902 - accuracy: 0.3800\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.2452 - accuracy: 0.4796\n",
       "Epoch 92/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.2341 - accuracy: 0.4837WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 428ms/step - loss: 2.7937 - accuracy: 0.3856\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.2344 - accuracy: 0.4837\n",
       "Epoch 93/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.2122 - accuracy: 0.4875WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 432ms/step - loss: 2.7800 - accuracy: 0.3872\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 2.2124 - accuracy: 0.4874\n",
       "Epoch 94/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.1793 - accuracy: 0.4960WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 426ms/step - loss: 2.7438 - accuracy: 0.3915\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 2.1793 - accuracy: 0.4960\n",
       "Epoch 95/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.1565 - accuracy: 0.5007WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 432ms/step - loss: 2.6921 - accuracy: 0.4015\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.1566 - accuracy: 0.5006\n",
       "Epoch 96/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.1420 - accuracy: 0.5010WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 419ms/step - loss: 2.6720 - accuracy: 0.4024\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.1420 - accuracy: 0.5010\n",
       "Epoch 97/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.1189 - accuracy: 0.5081WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 428ms/step - loss: 2.6635 - accuracy: 0.4064\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.1189 - accuracy: 0.5081\n",
       "Epoch 98/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.1183 - accuracy: 0.5060WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 427ms/step - loss: 2.6391 - accuracy: 0.4114\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 2.1186 - accuracy: 0.5060\n",
       "Epoch 99/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.0925 - accuracy: 0.5143WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 425ms/step - loss: 2.6089 - accuracy: 0.4195\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 2.0924 - accuracy: 0.5143\n",
       "Epoch 100/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.0765 - accuracy: 0.5176WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 427ms/step - loss: 2.5940 - accuracy: 0.4214\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.0764 - accuracy: 0.5177\n",
       "Epoch 101/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.0518 - accuracy: 0.5211WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 420ms/step - loss: 2.6007 - accuracy: 0.4165\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.0518 - accuracy: 0.5211\n",
       "Epoch 102/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.0427 - accuracy: 0.5235WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 430ms/step - loss: 2.5773 - accuracy: 0.4251\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.0425 - accuracy: 0.5235\n",
       "Epoch 103/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 2.0103 - accuracy: 0.5310WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 2.0104 - accuracy: 0.5309\n",
-      "Epoch 104/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.9949 - accuracy: 0.5353WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 425ms/step - loss: 2.5022 - accuracy: 0.4404\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.9947 - accuracy: 0.5354\n",
-      "Epoch 105/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.9812 - accuracy: 0.5350WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.9813 - accuracy: 0.5350\n",
       "Epoch 106/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.9673 - accuracy: 0.5397WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 428ms/step - loss: 2.5159 - accuracy: 0.4303\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.9677 - accuracy: 0.5396\n",
       "Epoch 107/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.9609 - accuracy: 0.5386WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 420ms/step - loss: 2.4863 - accuracy: 0.4394\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.9611 - accuracy: 0.5386\n",
       "Epoch 108/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.9310 - accuracy: 0.5461WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 418ms/step - loss: 2.4559 - accuracy: 0.4437\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.9313 - accuracy: 0.5460\n",
       "Epoch 109/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.9283 - accuracy: 0.5480WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 416ms/step - loss: 2.4468 - accuracy: 0.4514\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.9284 - accuracy: 0.5479\n",
       "Epoch 110/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.8997 - accuracy: 0.5525WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 417ms/step - loss: 2.4177 - accuracy: 0.4559\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.8997 - accuracy: 0.5525\n",
       "Epoch 111/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.8885 - accuracy: 0.5559WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 59s 447ms/step - loss: 2.3912 - accuracy: 0.4600\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.8887 - accuracy: 0.5559\n",
       "Epoch 112/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.8712 - accuracy: 0.5583WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 427ms/step - loss: 2.4065 - accuracy: 0.4563\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.8712 - accuracy: 0.5583\n",
       "Epoch 113/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.8687 - accuracy: 0.5610WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 426ms/step - loss: 2.3897 - accuracy: 0.4565\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.8686 - accuracy: 0.5611\n",
       "Epoch 114/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.8495 - accuracy: 0.5645WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 426ms/step - loss: 2.3525 - accuracy: 0.4678\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.8495 - accuracy: 0.5645\n",
       "Epoch 115/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.8277 - accuracy: 0.5694WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 422ms/step - loss: 2.3348 - accuracy: 0.4693\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.8275 - accuracy: 0.5695\n",
       "Epoch 116/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.8087 - accuracy: 0.5715WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 419ms/step - loss: 2.3347 - accuracy: 0.4687\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.8084 - accuracy: 0.5716\n",
       "Epoch 117/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.7855 - accuracy: 0.5787WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 425ms/step - loss: 2.3207 - accuracy: 0.4726\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.7852 - accuracy: 0.5788\n",
       "Epoch 118/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.7622 - accuracy: 0.5824WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 423ms/step - loss: 2.3181 - accuracy: 0.4755\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.7620 - accuracy: 0.5823\n",
       "Epoch 119/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.7621 - accuracy: 0.5810WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 428ms/step - loss: 2.2980 - accuracy: 0.4753\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.7619 - accuracy: 0.5810\n",
       "Epoch 120/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.7591 - accuracy: 0.5838WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.7592 - accuracy: 0.5837\n",
-      "Epoch 121/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.7241 - accuracy: 0.5911WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 417ms/step - loss: 2.2157 - accuracy: 0.4948\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 1.7242 - accuracy: 0.5910\n",
-      "Epoch 122/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.7056 - accuracy: 0.5967WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 1.7059 - accuracy: 0.5966\n",
       "Epoch 123/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.7064 - accuracy: 0.5963WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 420ms/step - loss: 2.2115 - accuracy: 0.4941\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 1.7064 - accuracy: 0.5963\n",
       "Epoch 124/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.6958 - accuracy: 0.5958WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 417ms/step - loss: 2.1935 - accuracy: 0.4993\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.6960 - accuracy: 0.5957\n",
       "Epoch 125/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.6797 - accuracy: 0.6000WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 421ms/step - loss: 2.1781 - accuracy: 0.5025\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.6800 - accuracy: 0.6000\n",
       "Epoch 126/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.6657 - accuracy: 0.6036WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 422ms/step - loss: 2.1532 - accuracy: 0.5066\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.6660 - accuracy: 0.6036\n",
       "Epoch 127/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.6428 - accuracy: 0.6090WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 430ms/step - loss: 2.1849 - accuracy: 0.5043\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 1.6426 - accuracy: 0.6091\n",
       "Epoch 128/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.6215 - accuracy: 0.6142WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 425ms/step - loss: 2.1639 - accuracy: 0.5044\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 1.6215 - accuracy: 0.6142\n",
       "Epoch 129/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.6349 - accuracy: 0.6091WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 422ms/step - loss: 2.1438 - accuracy: 0.5094\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.6348 - accuracy: 0.6091\n",
       "Epoch 130/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.6177 - accuracy: 0.6121WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 416ms/step - loss: 2.1359 - accuracy: 0.5084\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.6178 - accuracy: 0.6120\n",
       "Epoch 131/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.5900 - accuracy: 0.6198WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 415ms/step - loss: 2.1100 - accuracy: 0.5163\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.5900 - accuracy: 0.6198\n",
       "Epoch 132/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.5646 - accuracy: 0.6270WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 415ms/step - loss: 2.1135 - accuracy: 0.5133\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.5643 - accuracy: 0.6271\n",
       "Epoch 133/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.5621 - accuracy: 0.6268WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 416ms/step - loss: 2.0770 - accuracy: 0.5220\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.5622 - accuracy: 0.6268\n",
       "Epoch 134/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.5661 - accuracy: 0.6259WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 419ms/step - loss: 2.0623 - accuracy: 0.5288\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.5663 - accuracy: 0.6258\n",
       "Epoch 135/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.5490 - accuracy: 0.6277WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 416ms/step - loss: 2.0499 - accuracy: 0.5310\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 1.5489 - accuracy: 0.6277\n",
       "Epoch 136/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.5199 - accuracy: 0.6350WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 419ms/step - loss: 2.0152 - accuracy: 0.5345\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.5198 - accuracy: 0.6350\n",
       "Epoch 137/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.5261 - accuracy: 0.6338WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.5261 - accuracy: 0.6338\n",
-      "Epoch 138/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.4908 - accuracy: 0.6413WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 416ms/step - loss: 1.9802 - accuracy: 0.5395\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 1.4905 - accuracy: 0.6414\n",
-      "Epoch 139/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.4639 - accuracy: 0.6512WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.4637 - accuracy: 0.6513\n",
       "Epoch 140/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.4618 - accuracy: 0.6485WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 421ms/step - loss: 1.9752 - accuracy: 0.5427\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.4618 - accuracy: 0.6485\n",
       "Epoch 141/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.4472 - accuracy: 0.6539WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 419ms/step - loss: 1.9391 - accuracy: 0.5509\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.4471 - accuracy: 0.6539\n",
       "Epoch 142/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.4373 - accuracy: 0.6557WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 413ms/step - loss: 1.9337 - accuracy: 0.5527\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 1.4372 - accuracy: 0.6557\n",
       "Epoch 143/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.4504 - accuracy: 0.6492WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 421ms/step - loss: 1.9276 - accuracy: 0.5578\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 1.4505 - accuracy: 0.6492\n",
       "Epoch 144/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.4328 - accuracy: 0.6540WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 421ms/step - loss: 1.9234 - accuracy: 0.5535\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.4330 - accuracy: 0.6539\n",
       "Epoch 145/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.4204 - accuracy: 0.6559WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 417ms/step - loss: 1.9193 - accuracy: 0.5537\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.4203 - accuracy: 0.6559\n",
       "Epoch 146/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.3985 - accuracy: 0.6629WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 421ms/step - loss: 1.9060 - accuracy: 0.5576\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.3986 - accuracy: 0.6629\n",
       "Epoch 147/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.3763 - accuracy: 0.6692WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 421ms/step - loss: 1.8979 - accuracy: 0.5598\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.3763 - accuracy: 0.6692\n",
       "Epoch 148/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.3575 - accuracy: 0.6757WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 421ms/step - loss: 1.8885 - accuracy: 0.5614\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.3575 - accuracy: 0.6757\n",
       "Epoch 149/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.3612 - accuracy: 0.6738WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 417ms/step - loss: 1.8624 - accuracy: 0.5694\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.3615 - accuracy: 0.6737\n",
       "Epoch 150/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.3751 - accuracy: 0.6689WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 422ms/step - loss: 1.8423 - accuracy: 0.5706\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.3752 - accuracy: 0.6689\n",
       "Epoch 151/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.3438 - accuracy: 0.6749WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 420ms/step - loss: 1.8343 - accuracy: 0.5763\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.3441 - accuracy: 0.6747\n",
       "Epoch 152/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.3398 - accuracy: 0.6752WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 422ms/step - loss: 1.8462 - accuracy: 0.5681\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.3397 - accuracy: 0.6752\n",
       "Epoch 153/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.3187 - accuracy: 0.6811WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 420ms/step - loss: 1.7947 - accuracy: 0.5865\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.3185 - accuracy: 0.6812\n",
       "Epoch 154/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.3064 - accuracy: 0.6835WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 1.3065 - accuracy: 0.6835\n",
-      "Epoch 155/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.2743 - accuracy: 0.6935WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 418ms/step - loss: 1.7829 - accuracy: 0.5840\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 49s 1ms/sample - loss: 1.2742 - accuracy: 0.6935\n",
-      "Epoch 156/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.2659 - accuracy: 0.6971WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 1.2661 - accuracy: 0.6971\n",
       "Epoch 157/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.2636 - accuracy: 0.6966WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 417ms/step - loss: 1.7587 - accuracy: 0.5913\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.2634 - accuracy: 0.6966\n",
       "Epoch 158/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.2448 - accuracy: 0.6991WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 423ms/step - loss: 1.7555 - accuracy: 0.5912\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.2450 - accuracy: 0.6991\n",
       "Epoch 159/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.2827 - accuracy: 0.6882WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 417ms/step - loss: 1.7260 - accuracy: 0.6018\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.2828 - accuracy: 0.6882\n",
       "Epoch 160/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.2369 - accuracy: 0.6989WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 416ms/step - loss: 1.7104 - accuracy: 0.6042\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.2370 - accuracy: 0.6989\n",
       "Epoch 161/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.2147 - accuracy: 0.7076WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 416ms/step - loss: 1.7247 - accuracy: 0.5957\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.2145 - accuracy: 0.7077\n",
       "Epoch 162/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.2147 - accuracy: 0.7052WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 427ms/step - loss: 1.7259 - accuracy: 0.5947\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 1.2147 - accuracy: 0.7052\n",
       "Epoch 163/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.2157 - accuracy: 0.7043WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 421ms/step - loss: 1.7131 - accuracy: 0.5977\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.2156 - accuracy: 0.7043\n",
       "Epoch 164/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.1859 - accuracy: 0.7139WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 415ms/step - loss: 1.6682 - accuracy: 0.6078\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 46s 1ms/sample - loss: 1.1859 - accuracy: 0.7138\n",
       "Epoch 165/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.1531 - accuracy: 0.7207WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 423ms/step - loss: 1.6635 - accuracy: 0.6108\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
+      "Epoch 166/200\n",
+      "132/132 [==============================] - 55s 417ms/step - loss: 1.6613 - accuracy: 0.6115\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.1531 - accuracy: 0.7208\n",
       "Epoch 167/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.1415 - accuracy: 0.7232WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 421ms/step - loss: 1.6536 - accuracy: 0.6116\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
+      "Epoch 168/200\n",
+      "132/132 [==============================] - 55s 419ms/step - loss: 1.6128 - accuracy: 0.6205\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
+      "Epoch 169/200\n",
+      "132/132 [==============================] - 56s 421ms/step - loss: 1.6097 - accuracy: 0.6237\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 46s 1ms/sample - loss: 1.1414 - accuracy: 0.7232\n",
       "Epoch 170/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.1168 - accuracy: 0.7312WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 424ms/step - loss: 1.6222 - accuracy: 0.6189\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 46s 1ms/sample - loss: 1.1166 - accuracy: 0.7312\n",
       "Epoch 171/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.1078 - accuracy: 0.7320WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 420ms/step - loss: 1.6095 - accuracy: 0.6254\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 46s 1ms/sample - loss: 1.1080 - accuracy: 0.7319\n",
       "Epoch 172/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.1192 - accuracy: 0.7290WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 414ms/step - loss: 1.6274 - accuracy: 0.6163\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 46s 1ms/sample - loss: 1.1190 - accuracy: 0.7291\n",
       "Epoch 173/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.1254 - accuracy: 0.7261WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 413ms/step - loss: 1.5866 - accuracy: 0.6268\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.1256 - accuracy: 0.7260\n",
       "Epoch 174/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.1307 - accuracy: 0.7236WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 422ms/step - loss: 1.5600 - accuracy: 0.6357\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.1307 - accuracy: 0.7236\n",
       "Epoch 175/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.0979 - accuracy: 0.7309WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 418ms/step - loss: 1.5425 - accuracy: 0.6405\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.0978 - accuracy: 0.7309\n",
       "Epoch 176/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.0695 - accuracy: 0.7407WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 57s 434ms/step - loss: 1.5464 - accuracy: 0.6387\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.0695 - accuracy: 0.7407\n",
       "Epoch 177/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.0534 - accuracy: 0.7440WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 425ms/step - loss: 1.5179 - accuracy: 0.6446\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.0534 - accuracy: 0.7440\n",
       "Epoch 178/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.0387 - accuracy: 0.7470WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 420ms/step - loss: 1.5122 - accuracy: 0.6463\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.0389 - accuracy: 0.7470\n",
       "Epoch 179/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.0216 - accuracy: 0.7530WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 421ms/step - loss: 1.5001 - accuracy: 0.6506\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.0216 - accuracy: 0.7529\n",
       "Epoch 180/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.0215 - accuracy: 0.7544WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 420ms/step - loss: 1.5218 - accuracy: 0.6420\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 48s 1ms/sample - loss: 1.0214 - accuracy: 0.7544\n",
       "Epoch 181/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.0024 - accuracy: 0.7589WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 423ms/step - loss: 1.5194 - accuracy: 0.6402\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.0024 - accuracy: 0.7589\n",
       "Epoch 182/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.0034 - accuracy: 0.7576WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 420ms/step - loss: 1.4864 - accuracy: 0.6476\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.0032 - accuracy: 0.7577\n",
       "Epoch 183/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.9853 - accuracy: 0.7616WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 424ms/step - loss: 1.4901 - accuracy: 0.6476\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.9855 - accuracy: 0.7615\n",
       "Epoch 184/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.9828 - accuracy: 0.7642WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 418ms/step - loss: 1.4642 - accuracy: 0.6517\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.9830 - accuracy: 0.7641\n",
       "Epoch 185/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.9833 - accuracy: 0.7598WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 419ms/step - loss: 1.4762 - accuracy: 0.6502\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.9837 - accuracy: 0.7597\n",
       "Epoch 186/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.9894 - accuracy: 0.7581WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 416ms/step - loss: 1.4711 - accuracy: 0.6515\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.9898 - accuracy: 0.7580\n",
       "Epoch 187/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 1.0017 - accuracy: 0.7554WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 418ms/step - loss: 1.4420 - accuracy: 0.6588\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 1.0016 - accuracy: 0.7554\n",
       "Epoch 188/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.9590 - accuracy: 0.7679WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 425ms/step - loss: 1.4111 - accuracy: 0.6648\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.9590 - accuracy: 0.7679\n",
       "Epoch 189/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.9440 - accuracy: 0.7728WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 56s 425ms/step - loss: 1.3902 - accuracy: 0.6764\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.9441 - accuracy: 0.7728\n",
       "Epoch 190/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.9322 - accuracy: 0.7750WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 420ms/step - loss: 1.4237 - accuracy: 0.6661\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.9323 - accuracy: 0.7750\n",
       "Epoch 191/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.9246 - accuracy: 0.7771WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 419ms/step - loss: 1.4434 - accuracy: 0.6619\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.9244 - accuracy: 0.7772\n",
       "Epoch 192/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.9264 - accuracy: 0.7781WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 418ms/step - loss: 1.4235 - accuracy: 0.6669\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.9264 - accuracy: 0.7781\n",
       "Epoch 193/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.9295 - accuracy: 0.7738WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 414ms/step - loss: 1.3799 - accuracy: 0.6731\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 46s 1ms/sample - loss: 0.9294 - accuracy: 0.7738\n",
       "Epoch 194/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.9172 - accuracy: 0.7759WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 419ms/step - loss: 1.3654 - accuracy: 0.6793\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.9172 - accuracy: 0.7760\n",
       "Epoch 195/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.8771 - accuracy: 0.7895WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 418ms/step - loss: 1.3519 - accuracy: 0.6821\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.8771 - accuracy: 0.7895\n",
       "Epoch 196/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.8834 - accuracy: 0.7864WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.8836 - accuracy: 0.7864\n",
-      "Epoch 197/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.8764 - accuracy: 0.7882WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 417ms/step - loss: 1.3331 - accuracy: 0.6854\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.8765 - accuracy: 0.7882\n",
-      "Epoch 198/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.8671 - accuracy: 0.7904WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.8670 - accuracy: 0.7904\n",
       "Epoch 199/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.8518 - accuracy: 0.7943WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "132/132 [==============================] - 55s 418ms/step - loss: 1.3044 - accuracy: 0.6926\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
       "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.8519 - accuracy: 0.7943\n",
       "Epoch 200/200\n",
-      "33536/33549 [============================>.] - ETA: 0s - loss: 0.8349 - accuracy: 0.8001WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
-      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n",
-      "33549/33549 [==============================] - 47s 1ms/sample - loss: 0.8348 - accuracy: 0.8001\n"
+      "132/132 [==============================] - 55s 416ms/step - loss: 1.3154 - accuracy: 0.6904\n",
+      "WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,accuracy\n",
+      "WARNING:tensorflow:Can save best model only with val_loss available, skipping.\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<tensorflow.python.keras.callbacks.History at 0x7fe36a0318d0>"
+       "<tensorflow.python.keras.callbacks.History at 0x7f169c488fd0>"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1403,7 +1362,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1436,7 +1395,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1469,7 +1428,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -1498,7 +1457,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1543,7 +1502,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "nach alter weise in brudersphären wettgesang und ihre vorgeschriebne reise vollendet sie mit donnergang ihr anblick giebt den engeln stärke wenn keiner sie ergründen mag die unbegreiflich hohen werke sind herrlich wie am ersten tag gabriel und schnell und unbegreiflich schnelle dreht sich umher der erde pracht es wechselt paradieseshelle mit\n",
+      "von starrer seide die hahnenfeder auf dem hut mit einem langen spitzen degen und rathe nun dir kurz und gut dergleichen gleichfalls anzulegen damit du losgebunden frey erfahrest was das leben sey faust in jedem kleide werd ich wohl die pein des engen erdelebens fühlen ich bin zu alt um nur\n",
       "\n"
      ]
     }
@@ -1575,10 +1534,10 @@
      "output_type": "stream",
      "text": [
       "(1, 50)\n",
-      "[[  52  506  592    9 2853 2854    1  252 2855  821 2856   12   17 2857\n",
-      "    21  952  399   16 1733 1734   34  448   12 1735  117    3 1259  659\n",
-      "  1260   57  512   25   75  390  132 2858    1  822    1 1259 1256 1261\n",
-      "    19  513    4  215 1736   13 1737 2859]]\n"
+      "[[  30 4037 2094    3 2095   26   27 2096   17   96  902 4038 2097    1\n",
+      "  4039   47   45  459    1  102 4040 4041 4042  288   11 4043  240 4044\n",
+      "    23    7  115  145   18    9  273 1091  451    2   61    3  690   49\n",
+      "   678 4045  752    2   65    8  616   69]]\n"
      ]
     }
    ],
@@ -1606,13 +1565,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[17]\n"
+      "[22]\n"
      ]
     }
    ],
    "source": [
     "# predict probabilities for each word\n",
-    "yhat = model.predict_classes(encoded, verbose=0)\n",
+    "yhat = np.argmax(model.predict(encoded, verbose=0), axis=-1)\n",
     "print(yhat)"
    ]
   },
@@ -1632,7 +1591,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "mit\n"
+      "mich\n"
      ]
     }
    ],
@@ -1710,14 +1669,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "tiefer schauervoller nacht es schäumt das meer in breiten flüssen am tiefen grund der felsen auf und fels und meer wird fortgerissen in ewig schnellem sphärenlauf michael und stürme brausen um die wette vom meer aufs land vom land aufs meer und bilden wüthend eine kette der tiefsten wirkung rings\n"
+      "retten ich sags euch nicht gewesen zwar ist er steht so wunderlich als spazier so realist nach hoher liegt faust das faust im schüler so ists ein anfang war doch das grab der sterbend seine buhle bist denn daß du gemeinschaft mephistopheles ich nur jemand teufel schaffen sie steht er\n"
      ]
     }
    ],
@@ -2205,7 +2164,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
@@ -2301,14 +2260,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Model: \"functional_1\"\n",
+      "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/vgg16/vgg16_weights_tf_dim_ordering_tf_kernels.h5\n",
+      "553467904/553467096 [==============================] - 5s 0us/step\n",
+      "Model: \"model\"\n",
       "_________________________________________________________________\n",
       "Layer (type)                 Output Shape              Param #   \n",
       "=================================================================\n",
@@ -2360,8 +2321,19 @@
       "Trainable params: 134,260,544\n",
       "Non-trainable params: 0\n",
       "_________________________________________________________________\n",
-      "None\n",
-      "Extracted Features: 8091\n"
+      "None\n"
+     ]
+    },
+    {
+     "ename": "FileNotFoundError",
+     "evalue": "[Errno 2] No such file or directory: 'Flicker8k_Dataset/'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-2-9545493bef71>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     39\u001b[0m \u001b[0;31m# extract features from all images\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     40\u001b[0m \u001b[0mdirectory\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'Flicker8k_Dataset/'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 41\u001b[0;31m \u001b[0mfeatures\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mextract_features\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdirectory\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     42\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Extracted Features: %d'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     43\u001b[0m \u001b[0;31m# save to file\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-2-9545493bef71>\u001b[0m in \u001b[0;36mextract_features\u001b[0;34m(directory)\u001b[0m\n\u001b[1;32m     18\u001b[0m     \u001b[0;31m# extract features from each photo\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     19\u001b[0m     \u001b[0mfeatures\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 20\u001b[0;31m     \u001b[0;32mfor\u001b[0m \u001b[0mname\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mlistdir\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdirectory\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     21\u001b[0m         \u001b[0;31m# load an image from file\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     22\u001b[0m         \u001b[0mfilename\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdirectory\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m'/'\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'Flicker8k_Dataset/'"
      ]
     }
    ],
-- 
GitLab