2203 lines
268 KiB
Plaintext
2203 lines
268 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 1,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import numpy as np\n",
|
|
"import pandas as pd\n",
|
|
"from gensim.models import Word2Vec\n",
|
|
"from gensim.utils import simple_preprocess\n",
|
|
"from sklearn.model_selection import train_test_split\n",
|
|
"from sklearn.metrics import accuracy_score, classification_report\n",
|
|
"from tensorflow.keras.models import Sequential\n",
|
|
"from tensorflow.keras.layers import Dense\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 2,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def build_corpus(file_list):\n",
|
|
" documents = []\n",
|
|
" for file in file_list:\n",
|
|
" with open(file, 'r', encoding=\"utf8\") as f:\n",
|
|
" for line in f:\n",
|
|
" processed_line = simple_preprocess(line)\n",
|
|
" documents.append(processed_line)\n",
|
|
" return documents"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def text_to_vector(text, model):\n",
|
|
" tokens = simple_preprocess(text)\n",
|
|
" word_vectors = [model.wv[token] for token in tokens if token in model.wv]\n",
|
|
" if word_vectors:\n",
|
|
" return np.mean(word_vectors, axis=0)\n",
|
|
" else:\n",
|
|
" return np.zeros(model.vector_size)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def read_text_file(filepath):\n",
|
|
" lines = []\n",
|
|
" with open(filepath, 'r', encoding=\"utf8\") as file:\n",
|
|
" for line in file:\n",
|
|
" lines.append(line.strip())\n",
|
|
" return lines"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def write_predictions_to_file(predictions, filepath):\n",
|
|
" with open(filepath, 'w', encoding=\"utf8\") as file:\n",
|
|
" for prediction in predictions:\n",
|
|
" file.write(f\"{prediction[0]}\\n\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 6,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Epoch 1/1000\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"c:\\Users\\mateu\\anaconda3\\lib\\site-packages\\keras\\src\\layers\\core\\dense.py:86: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
|
|
" super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 3ms/step - accuracy: 0.6695 - loss: 0.5541 - val_accuracy: 0.8258 - val_loss: 0.3704\n",
|
|
"Epoch 2/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8517 - loss: 0.3327 - val_accuracy: 0.8433 - val_loss: 0.3428\n",
|
|
"Epoch 3/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8496 - loss: 0.3206 - val_accuracy: 0.8313 - val_loss: 0.3492\n",
|
|
"Epoch 4/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8634 - loss: 0.2961 - val_accuracy: 0.8414 - val_loss: 0.3361\n",
|
|
"Epoch 5/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8571 - loss: 0.3020 - val_accuracy: 0.8442 - val_loss: 0.3439\n",
|
|
"Epoch 6/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8655 - loss: 0.2932 - val_accuracy: 0.8368 - val_loss: 0.3387\n",
|
|
"Epoch 7/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8744 - loss: 0.2790 - val_accuracy: 0.8313 - val_loss: 0.3474\n",
|
|
"Epoch 8/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8717 - loss: 0.2764 - val_accuracy: 0.8543 - val_loss: 0.3247\n",
|
|
"Epoch 9/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8669 - loss: 0.2731 - val_accuracy: 0.8478 - val_loss: 0.3360\n",
|
|
"Epoch 10/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8642 - loss: 0.2950 - val_accuracy: 0.8515 - val_loss: 0.3323\n",
|
|
"Epoch 11/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8670 - loss: 0.2797 - val_accuracy: 0.8579 - val_loss: 0.3148\n",
|
|
"Epoch 12/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8736 - loss: 0.2718 - val_accuracy: 0.8561 - val_loss: 0.3161\n",
|
|
"Epoch 13/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8650 - loss: 0.2835 - val_accuracy: 0.8552 - val_loss: 0.3130\n",
|
|
"Epoch 14/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8709 - loss: 0.2772 - val_accuracy: 0.8561 - val_loss: 0.3146\n",
|
|
"Epoch 15/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8787 - loss: 0.2575 - val_accuracy: 0.8313 - val_loss: 0.3488\n",
|
|
"Epoch 16/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8690 - loss: 0.2716 - val_accuracy: 0.8570 - val_loss: 0.3126\n",
|
|
"Epoch 17/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8757 - loss: 0.2791 - val_accuracy: 0.8579 - val_loss: 0.3060\n",
|
|
"Epoch 18/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8799 - loss: 0.2637 - val_accuracy: 0.8286 - val_loss: 0.3696\n",
|
|
"Epoch 19/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8711 - loss: 0.2741 - val_accuracy: 0.8588 - val_loss: 0.3126\n",
|
|
"Epoch 20/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8728 - loss: 0.2667 - val_accuracy: 0.8588 - val_loss: 0.3104\n",
|
|
"Epoch 21/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8786 - loss: 0.2623 - val_accuracy: 0.8625 - val_loss: 0.3045\n",
|
|
"Epoch 22/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8685 - loss: 0.2739 - val_accuracy: 0.8616 - val_loss: 0.3074\n",
|
|
"Epoch 23/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8856 - loss: 0.2596 - val_accuracy: 0.8607 - val_loss: 0.3026\n",
|
|
"Epoch 24/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8819 - loss: 0.2513 - val_accuracy: 0.8460 - val_loss: 0.3318\n",
|
|
"Epoch 25/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8788 - loss: 0.2670 - val_accuracy: 0.8598 - val_loss: 0.3004\n",
|
|
"Epoch 26/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8875 - loss: 0.2411 - val_accuracy: 0.8607 - val_loss: 0.3046\n",
|
|
"Epoch 27/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8728 - loss: 0.2773 - val_accuracy: 0.8570 - val_loss: 0.3078\n",
|
|
"Epoch 28/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8733 - loss: 0.2631 - val_accuracy: 0.8598 - val_loss: 0.2978\n",
|
|
"Epoch 29/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8817 - loss: 0.2624 - val_accuracy: 0.8570 - val_loss: 0.2989\n",
|
|
"Epoch 30/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8868 - loss: 0.2405 - val_accuracy: 0.8598 - val_loss: 0.3063\n",
|
|
"Epoch 31/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8782 - loss: 0.2612 - val_accuracy: 0.8662 - val_loss: 0.3172\n",
|
|
"Epoch 32/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8790 - loss: 0.2623 - val_accuracy: 0.8634 - val_loss: 0.2906\n",
|
|
"Epoch 33/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8743 - loss: 0.2586 - val_accuracy: 0.8607 - val_loss: 0.3055\n",
|
|
"Epoch 34/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8822 - loss: 0.2609 - val_accuracy: 0.8616 - val_loss: 0.3042\n",
|
|
"Epoch 35/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8830 - loss: 0.2508 - val_accuracy: 0.8607 - val_loss: 0.3090\n",
|
|
"Epoch 36/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8905 - loss: 0.2489 - val_accuracy: 0.8607 - val_loss: 0.2981\n",
|
|
"Epoch 37/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8826 - loss: 0.2505 - val_accuracy: 0.8625 - val_loss: 0.3003\n",
|
|
"Epoch 38/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8894 - loss: 0.2444 - val_accuracy: 0.8653 - val_loss: 0.2879\n",
|
|
"Epoch 39/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8826 - loss: 0.2530 - val_accuracy: 0.8598 - val_loss: 0.3056\n",
|
|
"Epoch 40/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8901 - loss: 0.2478 - val_accuracy: 0.8625 - val_loss: 0.2877\n",
|
|
"Epoch 41/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8918 - loss: 0.2420 - val_accuracy: 0.8671 - val_loss: 0.3057\n",
|
|
"Epoch 42/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8782 - loss: 0.2495 - val_accuracy: 0.8598 - val_loss: 0.3100\n",
|
|
"Epoch 43/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8762 - loss: 0.2696 - val_accuracy: 0.8671 - val_loss: 0.2878\n",
|
|
"Epoch 44/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8848 - loss: 0.2449 - val_accuracy: 0.8671 - val_loss: 0.2874\n",
|
|
"Epoch 45/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8815 - loss: 0.2522 - val_accuracy: 0.8726 - val_loss: 0.2847\n",
|
|
"Epoch 46/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8877 - loss: 0.2450 - val_accuracy: 0.8469 - val_loss: 0.3448\n",
|
|
"Epoch 47/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8884 - loss: 0.2631 - val_accuracy: 0.8561 - val_loss: 0.3236\n",
|
|
"Epoch 48/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8840 - loss: 0.2530 - val_accuracy: 0.8680 - val_loss: 0.2843\n",
|
|
"Epoch 49/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8868 - loss: 0.2437 - val_accuracy: 0.8662 - val_loss: 0.2856\n",
|
|
"Epoch 50/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8824 - loss: 0.2461 - val_accuracy: 0.8662 - val_loss: 0.2875\n",
|
|
"Epoch 51/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8826 - loss: 0.2454 - val_accuracy: 0.8671 - val_loss: 0.2905\n",
|
|
"Epoch 52/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8888 - loss: 0.2399 - val_accuracy: 0.8708 - val_loss: 0.2866\n",
|
|
"Epoch 53/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8856 - loss: 0.2471 - val_accuracy: 0.8717 - val_loss: 0.2832\n",
|
|
"Epoch 54/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8953 - loss: 0.2306 - val_accuracy: 0.8671 - val_loss: 0.2843\n",
|
|
"Epoch 55/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8931 - loss: 0.2271 - val_accuracy: 0.8708 - val_loss: 0.2883\n",
|
|
"Epoch 56/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8865 - loss: 0.2468 - val_accuracy: 0.8643 - val_loss: 0.2837\n",
|
|
"Epoch 57/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8905 - loss: 0.2391 - val_accuracy: 0.8708 - val_loss: 0.2781\n",
|
|
"Epoch 58/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8894 - loss: 0.2494 - val_accuracy: 0.8689 - val_loss: 0.2833\n",
|
|
"Epoch 59/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8942 - loss: 0.2285 - val_accuracy: 0.8708 - val_loss: 0.2843\n",
|
|
"Epoch 60/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8928 - loss: 0.2375 - val_accuracy: 0.8671 - val_loss: 0.2963\n",
|
|
"Epoch 61/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8939 - loss: 0.2299 - val_accuracy: 0.8680 - val_loss: 0.2898\n",
|
|
"Epoch 62/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8889 - loss: 0.2354 - val_accuracy: 0.8708 - val_loss: 0.2799\n",
|
|
"Epoch 63/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8889 - loss: 0.2359 - val_accuracy: 0.8671 - val_loss: 0.2820\n",
|
|
"Epoch 64/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8848 - loss: 0.2457 - val_accuracy: 0.8698 - val_loss: 0.2796\n",
|
|
"Epoch 65/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9009 - loss: 0.2236 - val_accuracy: 0.8781 - val_loss: 0.2799\n",
|
|
"Epoch 66/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8939 - loss: 0.2306 - val_accuracy: 0.8680 - val_loss: 0.2800\n",
|
|
"Epoch 67/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8848 - loss: 0.2428 - val_accuracy: 0.8708 - val_loss: 0.2762\n",
|
|
"Epoch 68/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8942 - loss: 0.2369 - val_accuracy: 0.8726 - val_loss: 0.2747\n",
|
|
"Epoch 69/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8931 - loss: 0.2317 - val_accuracy: 0.8708 - val_loss: 0.2821\n",
|
|
"Epoch 70/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8877 - loss: 0.2368 - val_accuracy: 0.8735 - val_loss: 0.2736\n",
|
|
"Epoch 71/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8896 - loss: 0.2465 - val_accuracy: 0.8708 - val_loss: 0.2758\n",
|
|
"Epoch 72/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8951 - loss: 0.2335 - val_accuracy: 0.8726 - val_loss: 0.2821\n",
|
|
"Epoch 73/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8914 - loss: 0.2334 - val_accuracy: 0.8680 - val_loss: 0.2973\n",
|
|
"Epoch 74/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8905 - loss: 0.2378 - val_accuracy: 0.8763 - val_loss: 0.2763\n",
|
|
"Epoch 75/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8928 - loss: 0.2287 - val_accuracy: 0.8763 - val_loss: 0.2735\n",
|
|
"Epoch 76/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8937 - loss: 0.2369 - val_accuracy: 0.8726 - val_loss: 0.2935\n",
|
|
"Epoch 77/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8804 - loss: 0.2561 - val_accuracy: 0.8753 - val_loss: 0.2910\n",
|
|
"Epoch 78/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8861 - loss: 0.2370 - val_accuracy: 0.8662 - val_loss: 0.2999\n",
|
|
"Epoch 79/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8879 - loss: 0.2394 - val_accuracy: 0.8735 - val_loss: 0.2887\n",
|
|
"Epoch 80/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8866 - loss: 0.2442 - val_accuracy: 0.8744 - val_loss: 0.2738\n",
|
|
"Epoch 81/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8819 - loss: 0.2450 - val_accuracy: 0.8735 - val_loss: 0.2935\n",
|
|
"Epoch 82/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8905 - loss: 0.2407 - val_accuracy: 0.8643 - val_loss: 0.2967\n",
|
|
"Epoch 83/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8804 - loss: 0.2424 - val_accuracy: 0.8717 - val_loss: 0.2720\n",
|
|
"Epoch 84/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8935 - loss: 0.2295 - val_accuracy: 0.8680 - val_loss: 0.2961\n",
|
|
"Epoch 85/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8884 - loss: 0.2331 - val_accuracy: 0.8698 - val_loss: 0.2751\n",
|
|
"Epoch 86/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8943 - loss: 0.2282 - val_accuracy: 0.8735 - val_loss: 0.2669\n",
|
|
"Epoch 87/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8954 - loss: 0.2188 - val_accuracy: 0.8726 - val_loss: 0.2698\n",
|
|
"Epoch 88/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9015 - loss: 0.2225 - val_accuracy: 0.8836 - val_loss: 0.2658\n",
|
|
"Epoch 89/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8878 - loss: 0.2319 - val_accuracy: 0.8799 - val_loss: 0.2670\n",
|
|
"Epoch 90/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8966 - loss: 0.2383 - val_accuracy: 0.8708 - val_loss: 0.2746\n",
|
|
"Epoch 91/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8940 - loss: 0.2270 - val_accuracy: 0.8744 - val_loss: 0.2786\n",
|
|
"Epoch 92/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8899 - loss: 0.2372 - val_accuracy: 0.8772 - val_loss: 0.2681\n",
|
|
"Epoch 93/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8937 - loss: 0.2258 - val_accuracy: 0.8753 - val_loss: 0.2687\n",
|
|
"Epoch 94/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8975 - loss: 0.2207 - val_accuracy: 0.8717 - val_loss: 0.2676\n",
|
|
"Epoch 95/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8967 - loss: 0.2250 - val_accuracy: 0.8753 - val_loss: 0.2756\n",
|
|
"Epoch 96/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8971 - loss: 0.2244 - val_accuracy: 0.8735 - val_loss: 0.2719\n",
|
|
"Epoch 97/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8945 - loss: 0.2208 - val_accuracy: 0.8726 - val_loss: 0.2784\n",
|
|
"Epoch 98/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9031 - loss: 0.2222 - val_accuracy: 0.8726 - val_loss: 0.2691\n",
|
|
"Epoch 99/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8954 - loss: 0.2350 - val_accuracy: 0.8735 - val_loss: 0.2868\n",
|
|
"Epoch 100/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8949 - loss: 0.2221 - val_accuracy: 0.8799 - val_loss: 0.2691\n",
|
|
"Epoch 101/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8899 - loss: 0.2273 - val_accuracy: 0.8763 - val_loss: 0.2775\n",
|
|
"Epoch 102/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8956 - loss: 0.2256 - val_accuracy: 0.8717 - val_loss: 0.2831\n",
|
|
"Epoch 103/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9027 - loss: 0.2257 - val_accuracy: 0.8763 - val_loss: 0.2738\n",
|
|
"Epoch 104/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9048 - loss: 0.2026 - val_accuracy: 0.8634 - val_loss: 0.2977\n",
|
|
"Epoch 105/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9056 - loss: 0.2171 - val_accuracy: 0.8689 - val_loss: 0.2877\n",
|
|
"Epoch 106/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9011 - loss: 0.2218 - val_accuracy: 0.8854 - val_loss: 0.2730\n",
|
|
"Epoch 107/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8927 - loss: 0.2302 - val_accuracy: 0.8772 - val_loss: 0.2653\n",
|
|
"Epoch 108/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9050 - loss: 0.2031 - val_accuracy: 0.8790 - val_loss: 0.2738\n",
|
|
"Epoch 109/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9087 - loss: 0.2103 - val_accuracy: 0.8836 - val_loss: 0.2688\n",
|
|
"Epoch 110/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9009 - loss: 0.2136 - val_accuracy: 0.8744 - val_loss: 0.2690\n",
|
|
"Epoch 111/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8956 - loss: 0.2290 - val_accuracy: 0.8735 - val_loss: 0.2859\n",
|
|
"Epoch 112/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9020 - loss: 0.2150 - val_accuracy: 0.8818 - val_loss: 0.2643\n",
|
|
"Epoch 113/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9015 - loss: 0.2180 - val_accuracy: 0.8808 - val_loss: 0.2858\n",
|
|
"Epoch 114/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9040 - loss: 0.2096 - val_accuracy: 0.8717 - val_loss: 0.2748\n",
|
|
"Epoch 115/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8998 - loss: 0.2145 - val_accuracy: 0.8772 - val_loss: 0.2629\n",
|
|
"Epoch 116/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9027 - loss: 0.2109 - val_accuracy: 0.8753 - val_loss: 0.2662\n",
|
|
"Epoch 117/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8993 - loss: 0.2232 - val_accuracy: 0.8799 - val_loss: 0.2606\n",
|
|
"Epoch 118/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8953 - loss: 0.2237 - val_accuracy: 0.8799 - val_loss: 0.2730\n",
|
|
"Epoch 119/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9001 - loss: 0.2300 - val_accuracy: 0.8845 - val_loss: 0.2627\n",
|
|
"Epoch 120/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9031 - loss: 0.2078 - val_accuracy: 0.8781 - val_loss: 0.2654\n",
|
|
"Epoch 121/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8929 - loss: 0.2277 - val_accuracy: 0.8818 - val_loss: 0.2690\n",
|
|
"Epoch 122/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8945 - loss: 0.2231 - val_accuracy: 0.8763 - val_loss: 0.2725\n",
|
|
"Epoch 123/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9029 - loss: 0.2125 - val_accuracy: 0.8781 - val_loss: 0.2716\n",
|
|
"Epoch 124/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9049 - loss: 0.2122 - val_accuracy: 0.8790 - val_loss: 0.2687\n",
|
|
"Epoch 125/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8994 - loss: 0.2090 - val_accuracy: 0.8680 - val_loss: 0.2960\n",
|
|
"Epoch 126/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8924 - loss: 0.2325 - val_accuracy: 0.8671 - val_loss: 0.3063\n",
|
|
"Epoch 127/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9012 - loss: 0.2226 - val_accuracy: 0.8781 - val_loss: 0.2700\n",
|
|
"Epoch 128/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9030 - loss: 0.2105 - val_accuracy: 0.8598 - val_loss: 0.2991\n",
|
|
"Epoch 129/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.8984 - loss: 0.2157 - val_accuracy: 0.8781 - val_loss: 0.2673\n",
|
|
"Epoch 130/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9007 - loss: 0.2159 - val_accuracy: 0.8845 - val_loss: 0.2697\n",
|
|
"Epoch 131/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9049 - loss: 0.2089 - val_accuracy: 0.8772 - val_loss: 0.2693\n",
|
|
"Epoch 132/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9036 - loss: 0.2157 - val_accuracy: 0.8799 - val_loss: 0.2741\n",
|
|
"Epoch 133/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9062 - loss: 0.2093 - val_accuracy: 0.8836 - val_loss: 0.2623\n",
|
|
"Epoch 134/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9022 - loss: 0.2077 - val_accuracy: 0.8827 - val_loss: 0.2680\n",
|
|
"Epoch 135/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9005 - loss: 0.2125 - val_accuracy: 0.8772 - val_loss: 0.2646\n",
|
|
"Epoch 136/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9108 - loss: 0.2043 - val_accuracy: 0.8827 - val_loss: 0.2763\n",
|
|
"Epoch 137/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9061 - loss: 0.2135 - val_accuracy: 0.8873 - val_loss: 0.2587\n",
|
|
"Epoch 138/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8985 - loss: 0.2229 - val_accuracy: 0.8781 - val_loss: 0.2951\n",
|
|
"Epoch 139/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8835 - loss: 0.2445 - val_accuracy: 0.8799 - val_loss: 0.2627\n",
|
|
"Epoch 140/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9022 - loss: 0.2191 - val_accuracy: 0.8808 - val_loss: 0.2653\n",
|
|
"Epoch 141/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8941 - loss: 0.2335 - val_accuracy: 0.8818 - val_loss: 0.2671\n",
|
|
"Epoch 142/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9021 - loss: 0.2220 - val_accuracy: 0.8845 - val_loss: 0.2617\n",
|
|
"Epoch 143/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9083 - loss: 0.2041 - val_accuracy: 0.8836 - val_loss: 0.2705\n",
|
|
"Epoch 144/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9046 - loss: 0.2086 - val_accuracy: 0.8854 - val_loss: 0.2607\n",
|
|
"Epoch 145/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9100 - loss: 0.2101 - val_accuracy: 0.8891 - val_loss: 0.2722\n",
|
|
"Epoch 146/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9048 - loss: 0.2144 - val_accuracy: 0.8836 - val_loss: 0.2664\n",
|
|
"Epoch 147/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9072 - loss: 0.2056 - val_accuracy: 0.8836 - val_loss: 0.2673\n",
|
|
"Epoch 148/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8990 - loss: 0.2224 - val_accuracy: 0.8836 - val_loss: 0.2617\n",
|
|
"Epoch 149/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8964 - loss: 0.2230 - val_accuracy: 0.8808 - val_loss: 0.2771\n",
|
|
"Epoch 150/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9038 - loss: 0.2052 - val_accuracy: 0.8900 - val_loss: 0.2670\n",
|
|
"Epoch 151/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9087 - loss: 0.2023 - val_accuracy: 0.8845 - val_loss: 0.2647\n",
|
|
"Epoch 152/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8963 - loss: 0.2146 - val_accuracy: 0.8909 - val_loss: 0.2637\n",
|
|
"Epoch 153/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9039 - loss: 0.2086 - val_accuracy: 0.8827 - val_loss: 0.2647\n",
|
|
"Epoch 154/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9065 - loss: 0.2134 - val_accuracy: 0.8772 - val_loss: 0.2786\n",
|
|
"Epoch 155/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8996 - loss: 0.2232 - val_accuracy: 0.8836 - val_loss: 0.2664\n",
|
|
"Epoch 156/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9088 - loss: 0.2097 - val_accuracy: 0.8689 - val_loss: 0.2887\n",
|
|
"Epoch 157/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9028 - loss: 0.2188 - val_accuracy: 0.8790 - val_loss: 0.2737\n",
|
|
"Epoch 158/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9083 - loss: 0.2065 - val_accuracy: 0.8763 - val_loss: 0.2722\n",
|
|
"Epoch 159/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9052 - loss: 0.2041 - val_accuracy: 0.8845 - val_loss: 0.2772\n",
|
|
"Epoch 160/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9087 - loss: 0.2130 - val_accuracy: 0.8854 - val_loss: 0.2727\n",
|
|
"Epoch 161/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9030 - loss: 0.2091 - val_accuracy: 0.8662 - val_loss: 0.3082\n",
|
|
"Epoch 162/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9025 - loss: 0.2149 - val_accuracy: 0.8818 - val_loss: 0.2666\n",
|
|
"Epoch 163/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9007 - loss: 0.2126 - val_accuracy: 0.8882 - val_loss: 0.2720\n",
|
|
"Epoch 164/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9036 - loss: 0.2210 - val_accuracy: 0.8891 - val_loss: 0.2630\n",
|
|
"Epoch 165/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8998 - loss: 0.2112 - val_accuracy: 0.8900 - val_loss: 0.2567\n",
|
|
"Epoch 166/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9036 - loss: 0.2241 - val_accuracy: 0.8873 - val_loss: 0.2666\n",
|
|
"Epoch 167/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9059 - loss: 0.2109 - val_accuracy: 0.8836 - val_loss: 0.2771\n",
|
|
"Epoch 168/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9026 - loss: 0.2143 - val_accuracy: 0.8827 - val_loss: 0.2680\n",
|
|
"Epoch 169/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9130 - loss: 0.1934 - val_accuracy: 0.8873 - val_loss: 0.2643\n",
|
|
"Epoch 170/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8920 - loss: 0.2272 - val_accuracy: 0.8863 - val_loss: 0.2647\n",
|
|
"Epoch 171/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9054 - loss: 0.2128 - val_accuracy: 0.8873 - val_loss: 0.2600\n",
|
|
"Epoch 172/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9070 - loss: 0.2026 - val_accuracy: 0.8900 - val_loss: 0.2581\n",
|
|
"Epoch 173/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9001 - loss: 0.2152 - val_accuracy: 0.8845 - val_loss: 0.2585\n",
|
|
"Epoch 174/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9101 - loss: 0.2082 - val_accuracy: 0.8781 - val_loss: 0.2773\n",
|
|
"Epoch 175/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9066 - loss: 0.2163 - val_accuracy: 0.8845 - val_loss: 0.2673\n",
|
|
"Epoch 176/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9156 - loss: 0.1942 - val_accuracy: 0.8818 - val_loss: 0.2736\n",
|
|
"Epoch 177/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9030 - loss: 0.2067 - val_accuracy: 0.8726 - val_loss: 0.2855\n",
|
|
"Epoch 178/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9015 - loss: 0.2270 - val_accuracy: 0.8735 - val_loss: 0.2828\n",
|
|
"Epoch 179/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9068 - loss: 0.2097 - val_accuracy: 0.8753 - val_loss: 0.2844\n",
|
|
"Epoch 180/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9093 - loss: 0.2045 - val_accuracy: 0.8781 - val_loss: 0.2797\n",
|
|
"Epoch 181/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9106 - loss: 0.2079 - val_accuracy: 0.8799 - val_loss: 0.2795\n",
|
|
"Epoch 182/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9077 - loss: 0.2081 - val_accuracy: 0.8808 - val_loss: 0.2617\n",
|
|
"Epoch 183/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8979 - loss: 0.2151 - val_accuracy: 0.8909 - val_loss: 0.2600\n",
|
|
"Epoch 184/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9060 - loss: 0.2027 - val_accuracy: 0.8928 - val_loss: 0.2595\n",
|
|
"Epoch 185/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9071 - loss: 0.1985 - val_accuracy: 0.8909 - val_loss: 0.2628\n",
|
|
"Epoch 186/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9030 - loss: 0.2134 - val_accuracy: 0.8790 - val_loss: 0.2716\n",
|
|
"Epoch 187/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9042 - loss: 0.1951 - val_accuracy: 0.8873 - val_loss: 0.2690\n",
|
|
"Epoch 188/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9136 - loss: 0.2058 - val_accuracy: 0.8653 - val_loss: 0.2986\n",
|
|
"Epoch 189/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8865 - loss: 0.2381 - val_accuracy: 0.8863 - val_loss: 0.2595\n",
|
|
"Epoch 190/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9119 - loss: 0.1963 - val_accuracy: 0.8854 - val_loss: 0.2672\n",
|
|
"Epoch 191/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9038 - loss: 0.2089 - val_accuracy: 0.8909 - val_loss: 0.2556\n",
|
|
"Epoch 192/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9003 - loss: 0.2082 - val_accuracy: 0.8918 - val_loss: 0.2642\n",
|
|
"Epoch 193/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9007 - loss: 0.2127 - val_accuracy: 0.8891 - val_loss: 0.2597\n",
|
|
"Epoch 194/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9075 - loss: 0.2076 - val_accuracy: 0.8918 - val_loss: 0.2618\n",
|
|
"Epoch 195/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9022 - loss: 0.2064 - val_accuracy: 0.8946 - val_loss: 0.2659\n",
|
|
"Epoch 196/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9048 - loss: 0.2214 - val_accuracy: 0.8818 - val_loss: 0.2917\n",
|
|
"Epoch 197/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9068 - loss: 0.1978 - val_accuracy: 0.8900 - val_loss: 0.2594\n",
|
|
"Epoch 198/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9101 - loss: 0.2071 - val_accuracy: 0.8900 - val_loss: 0.2639\n",
|
|
"Epoch 199/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8983 - loss: 0.2111 - val_accuracy: 0.8854 - val_loss: 0.2678\n",
|
|
"Epoch 200/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9115 - loss: 0.2000 - val_accuracy: 0.8928 - val_loss: 0.2615\n",
|
|
"Epoch 201/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9095 - loss: 0.1994 - val_accuracy: 0.8882 - val_loss: 0.2639\n",
|
|
"Epoch 202/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9065 - loss: 0.2018 - val_accuracy: 0.8918 - val_loss: 0.2713\n",
|
|
"Epoch 203/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9022 - loss: 0.2078 - val_accuracy: 0.8863 - val_loss: 0.2617\n",
|
|
"Epoch 204/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9158 - loss: 0.2048 - val_accuracy: 0.8827 - val_loss: 0.2697\n",
|
|
"Epoch 205/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9006 - loss: 0.2129 - val_accuracy: 0.8799 - val_loss: 0.2750\n",
|
|
"Epoch 206/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9088 - loss: 0.2063 - val_accuracy: 0.8836 - val_loss: 0.2707\n",
|
|
"Epoch 207/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9111 - loss: 0.2016 - val_accuracy: 0.8854 - val_loss: 0.2706\n",
|
|
"Epoch 208/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9011 - loss: 0.2117 - val_accuracy: 0.8882 - val_loss: 0.2597\n",
|
|
"Epoch 209/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9015 - loss: 0.2017 - val_accuracy: 0.8891 - val_loss: 0.2687\n",
|
|
"Epoch 210/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9120 - loss: 0.2009 - val_accuracy: 0.8808 - val_loss: 0.2769\n",
|
|
"Epoch 211/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9110 - loss: 0.2000 - val_accuracy: 0.8836 - val_loss: 0.2698\n",
|
|
"Epoch 212/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9090 - loss: 0.1953 - val_accuracy: 0.8900 - val_loss: 0.2643\n",
|
|
"Epoch 213/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9139 - loss: 0.1932 - val_accuracy: 0.8808 - val_loss: 0.2778\n",
|
|
"Epoch 214/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9136 - loss: 0.1944 - val_accuracy: 0.8909 - val_loss: 0.2571\n",
|
|
"Epoch 215/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9066 - loss: 0.2005 - val_accuracy: 0.8854 - val_loss: 0.2720\n",
|
|
"Epoch 216/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9091 - loss: 0.2024 - val_accuracy: 0.8882 - val_loss: 0.2636\n",
|
|
"Epoch 217/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9154 - loss: 0.1851 - val_accuracy: 0.8882 - val_loss: 0.2775\n",
|
|
"Epoch 218/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9021 - loss: 0.2115 - val_accuracy: 0.8845 - val_loss: 0.2704\n",
|
|
"Epoch 219/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9098 - loss: 0.1989 - val_accuracy: 0.8891 - val_loss: 0.2642\n",
|
|
"Epoch 220/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9120 - loss: 0.1992 - val_accuracy: 0.8478 - val_loss: 0.3517\n",
|
|
"Epoch 221/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.8967 - loss: 0.2336 - val_accuracy: 0.8918 - val_loss: 0.2637\n",
|
|
"Epoch 222/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9099 - loss: 0.2053 - val_accuracy: 0.8818 - val_loss: 0.2788\n",
|
|
"Epoch 223/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9084 - loss: 0.2008 - val_accuracy: 0.8818 - val_loss: 0.2726\n",
|
|
"Epoch 224/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9027 - loss: 0.2092 - val_accuracy: 0.8882 - val_loss: 0.2743\n",
|
|
"Epoch 225/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9177 - loss: 0.1943 - val_accuracy: 0.8909 - val_loss: 0.2514\n",
|
|
"Epoch 226/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9106 - loss: 0.2034 - val_accuracy: 0.8918 - val_loss: 0.2650\n",
|
|
"Epoch 227/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9195 - loss: 0.1890 - val_accuracy: 0.8873 - val_loss: 0.2711\n",
|
|
"Epoch 228/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9181 - loss: 0.1900 - val_accuracy: 0.8937 - val_loss: 0.2612\n",
|
|
"Epoch 229/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9069 - loss: 0.1987 - val_accuracy: 0.8772 - val_loss: 0.2905\n",
|
|
"Epoch 230/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9096 - loss: 0.2033 - val_accuracy: 0.8863 - val_loss: 0.2744\n",
|
|
"Epoch 231/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9075 - loss: 0.2025 - val_accuracy: 0.8955 - val_loss: 0.2615\n",
|
|
"Epoch 232/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9139 - loss: 0.1935 - val_accuracy: 0.8781 - val_loss: 0.2783\n",
|
|
"Epoch 233/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9013 - loss: 0.2027 - val_accuracy: 0.8873 - val_loss: 0.2662\n",
|
|
"Epoch 234/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9092 - loss: 0.2061 - val_accuracy: 0.8827 - val_loss: 0.2689\n",
|
|
"Epoch 235/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9071 - loss: 0.1968 - val_accuracy: 0.8937 - val_loss: 0.2618\n",
|
|
"Epoch 236/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9180 - loss: 0.1938 - val_accuracy: 0.8744 - val_loss: 0.2797\n",
|
|
"Epoch 237/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9110 - loss: 0.1996 - val_accuracy: 0.8891 - val_loss: 0.2645\n",
|
|
"Epoch 238/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9163 - loss: 0.1893 - val_accuracy: 0.8827 - val_loss: 0.2781\n",
|
|
"Epoch 239/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9150 - loss: 0.1966 - val_accuracy: 0.8964 - val_loss: 0.2651\n",
|
|
"Epoch 240/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9150 - loss: 0.1859 - val_accuracy: 0.8937 - val_loss: 0.2538\n",
|
|
"Epoch 241/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9144 - loss: 0.1942 - val_accuracy: 0.8928 - val_loss: 0.2537\n",
|
|
"Epoch 242/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9212 - loss: 0.1837 - val_accuracy: 0.8946 - val_loss: 0.2595\n",
|
|
"Epoch 243/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9122 - loss: 0.1936 - val_accuracy: 0.8790 - val_loss: 0.2756\n",
|
|
"Epoch 244/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9114 - loss: 0.1958 - val_accuracy: 0.8918 - val_loss: 0.2546\n",
|
|
"Epoch 245/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9113 - loss: 0.1983 - val_accuracy: 0.8799 - val_loss: 0.2716\n",
|
|
"Epoch 246/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9166 - loss: 0.1890 - val_accuracy: 0.8937 - val_loss: 0.2635\n",
|
|
"Epoch 247/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9139 - loss: 0.1872 - val_accuracy: 0.8882 - val_loss: 0.2686\n",
|
|
"Epoch 248/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9061 - loss: 0.2019 - val_accuracy: 0.8891 - val_loss: 0.2707\n",
|
|
"Epoch 249/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9105 - loss: 0.1968 - val_accuracy: 0.8955 - val_loss: 0.2592\n",
|
|
"Epoch 250/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9211 - loss: 0.1891 - val_accuracy: 0.8790 - val_loss: 0.2843\n",
|
|
"Epoch 251/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9147 - loss: 0.1973 - val_accuracy: 0.8909 - val_loss: 0.2687\n",
|
|
"Epoch 252/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9117 - loss: 0.1970 - val_accuracy: 0.8900 - val_loss: 0.2699\n",
|
|
"Epoch 253/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9163 - loss: 0.1909 - val_accuracy: 0.8882 - val_loss: 0.2775\n",
|
|
"Epoch 254/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9085 - loss: 0.1998 - val_accuracy: 0.8873 - val_loss: 0.2670\n",
|
|
"Epoch 255/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9214 - loss: 0.1795 - val_accuracy: 0.8818 - val_loss: 0.2792\n",
|
|
"Epoch 256/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9130 - loss: 0.1912 - val_accuracy: 0.8808 - val_loss: 0.2709\n",
|
|
"Epoch 257/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9109 - loss: 0.1958 - val_accuracy: 0.8909 - val_loss: 0.2670\n",
|
|
"Epoch 258/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9100 - loss: 0.2043 - val_accuracy: 0.8891 - val_loss: 0.2737\n",
|
|
"Epoch 259/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9126 - loss: 0.1978 - val_accuracy: 0.8937 - val_loss: 0.2584\n",
|
|
"Epoch 260/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9165 - loss: 0.1918 - val_accuracy: 0.8845 - val_loss: 0.2720\n",
|
|
"Epoch 261/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9159 - loss: 0.1933 - val_accuracy: 0.8964 - val_loss: 0.2534\n",
|
|
"Epoch 262/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9131 - loss: 0.1979 - val_accuracy: 0.8983 - val_loss: 0.2582\n",
|
|
"Epoch 263/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9109 - loss: 0.1932 - val_accuracy: 0.8900 - val_loss: 0.2768\n",
|
|
"Epoch 264/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9151 - loss: 0.1920 - val_accuracy: 0.8900 - val_loss: 0.2587\n",
|
|
"Epoch 265/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9077 - loss: 0.2053 - val_accuracy: 0.8882 - val_loss: 0.2654\n",
|
|
"Epoch 266/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9191 - loss: 0.1924 - val_accuracy: 0.8937 - val_loss: 0.2573\n",
|
|
"Epoch 267/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9187 - loss: 0.1875 - val_accuracy: 0.8873 - val_loss: 0.2564\n",
|
|
"Epoch 268/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9049 - loss: 0.2044 - val_accuracy: 0.8891 - val_loss: 0.2667\n",
|
|
"Epoch 269/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9160 - loss: 0.1881 - val_accuracy: 0.8918 - val_loss: 0.2642\n",
|
|
"Epoch 270/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9170 - loss: 0.1873 - val_accuracy: 0.8873 - val_loss: 0.2709\n",
|
|
"Epoch 271/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9082 - loss: 0.1996 - val_accuracy: 0.8973 - val_loss: 0.2614\n",
|
|
"Epoch 272/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9144 - loss: 0.1837 - val_accuracy: 0.8946 - val_loss: 0.2696\n",
|
|
"Epoch 273/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9162 - loss: 0.1885 - val_accuracy: 0.8909 - val_loss: 0.2612\n",
|
|
"Epoch 274/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9158 - loss: 0.1880 - val_accuracy: 0.8836 - val_loss: 0.2797\n",
|
|
"Epoch 275/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9132 - loss: 0.1954 - val_accuracy: 0.8946 - val_loss: 0.2595\n",
|
|
"Epoch 276/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9139 - loss: 0.1946 - val_accuracy: 0.8781 - val_loss: 0.2963\n",
|
|
"Epoch 277/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9129 - loss: 0.1891 - val_accuracy: 0.8955 - val_loss: 0.2585\n",
|
|
"Epoch 278/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9171 - loss: 0.1834 - val_accuracy: 0.8836 - val_loss: 0.2670\n",
|
|
"Epoch 279/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9171 - loss: 0.1872 - val_accuracy: 0.8909 - val_loss: 0.2630\n",
|
|
"Epoch 280/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9105 - loss: 0.1957 - val_accuracy: 0.8928 - val_loss: 0.2722\n",
|
|
"Epoch 281/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9123 - loss: 0.1975 - val_accuracy: 0.8772 - val_loss: 0.2844\n",
|
|
"Epoch 282/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9104 - loss: 0.1956 - val_accuracy: 0.8937 - val_loss: 0.2634\n",
|
|
"Epoch 283/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9134 - loss: 0.2015 - val_accuracy: 0.8928 - val_loss: 0.2621\n",
|
|
"Epoch 284/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9191 - loss: 0.1942 - val_accuracy: 0.8863 - val_loss: 0.2584\n",
|
|
"Epoch 285/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9146 - loss: 0.1868 - val_accuracy: 0.8928 - val_loss: 0.2639\n",
|
|
"Epoch 286/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9144 - loss: 0.1940 - val_accuracy: 0.8863 - val_loss: 0.2699\n",
|
|
"Epoch 287/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9134 - loss: 0.1835 - val_accuracy: 0.8946 - val_loss: 0.2606\n",
|
|
"Epoch 288/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9152 - loss: 0.1875 - val_accuracy: 0.8918 - val_loss: 0.2598\n",
|
|
"Epoch 289/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9170 - loss: 0.1899 - val_accuracy: 0.8909 - val_loss: 0.2749\n",
|
|
"Epoch 290/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9101 - loss: 0.1968 - val_accuracy: 0.8873 - val_loss: 0.2709\n",
|
|
"Epoch 291/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9189 - loss: 0.1904 - val_accuracy: 0.8863 - val_loss: 0.2785\n",
|
|
"Epoch 292/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9015 - loss: 0.2084 - val_accuracy: 0.8863 - val_loss: 0.2656\n",
|
|
"Epoch 293/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9171 - loss: 0.1920 - val_accuracy: 0.8955 - val_loss: 0.2690\n",
|
|
"Epoch 294/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9153 - loss: 0.1972 - val_accuracy: 0.8891 - val_loss: 0.2651\n",
|
|
"Epoch 295/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9087 - loss: 0.1923 - val_accuracy: 0.8946 - val_loss: 0.2717\n",
|
|
"Epoch 296/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9122 - loss: 0.1853 - val_accuracy: 0.8863 - val_loss: 0.2659\n",
|
|
"Epoch 297/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9147 - loss: 0.1973 - val_accuracy: 0.8873 - val_loss: 0.2749\n",
|
|
"Epoch 298/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9227 - loss: 0.1757 - val_accuracy: 0.8909 - val_loss: 0.2722\n",
|
|
"Epoch 299/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9123 - loss: 0.1874 - val_accuracy: 0.8937 - val_loss: 0.2739\n",
|
|
"Epoch 300/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9161 - loss: 0.1928 - val_accuracy: 0.8790 - val_loss: 0.2913\n",
|
|
"Epoch 301/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9096 - loss: 0.1962 - val_accuracy: 0.8918 - val_loss: 0.2637\n",
|
|
"Epoch 302/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9210 - loss: 0.1793 - val_accuracy: 0.8937 - val_loss: 0.2716\n",
|
|
"Epoch 303/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9213 - loss: 0.1840 - val_accuracy: 0.8900 - val_loss: 0.2614\n",
|
|
"Epoch 304/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9093 - loss: 0.1934 - val_accuracy: 0.8973 - val_loss: 0.2669\n",
|
|
"Epoch 305/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9137 - loss: 0.1864 - val_accuracy: 0.8900 - val_loss: 0.2693\n",
|
|
"Epoch 306/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9125 - loss: 0.1951 - val_accuracy: 0.8937 - val_loss: 0.2631\n",
|
|
"Epoch 307/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9084 - loss: 0.1979 - val_accuracy: 0.8882 - val_loss: 0.2851\n",
|
|
"Epoch 308/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9075 - loss: 0.2001 - val_accuracy: 0.8909 - val_loss: 0.2660\n",
|
|
"Epoch 309/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9140 - loss: 0.1943 - val_accuracy: 0.8973 - val_loss: 0.2706\n",
|
|
"Epoch 310/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9189 - loss: 0.1899 - val_accuracy: 0.8891 - val_loss: 0.2674\n",
|
|
"Epoch 311/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9211 - loss: 0.1845 - val_accuracy: 0.8946 - val_loss: 0.2632\n",
|
|
"Epoch 312/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9183 - loss: 0.1814 - val_accuracy: 0.8955 - val_loss: 0.2632\n",
|
|
"Epoch 313/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9196 - loss: 0.1854 - val_accuracy: 0.8790 - val_loss: 0.2963\n",
|
|
"Epoch 314/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9196 - loss: 0.1841 - val_accuracy: 0.8928 - val_loss: 0.2621\n",
|
|
"Epoch 315/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9229 - loss: 0.1781 - val_accuracy: 0.8900 - val_loss: 0.2776\n",
|
|
"Epoch 316/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9146 - loss: 0.1921 - val_accuracy: 0.8900 - val_loss: 0.2648\n",
|
|
"Epoch 317/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9178 - loss: 0.1841 - val_accuracy: 0.8882 - val_loss: 0.2689\n",
|
|
"Epoch 318/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9208 - loss: 0.1828 - val_accuracy: 0.8827 - val_loss: 0.2782\n",
|
|
"Epoch 319/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9143 - loss: 0.1968 - val_accuracy: 0.8818 - val_loss: 0.2779\n",
|
|
"Epoch 320/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9119 - loss: 0.1843 - val_accuracy: 0.8955 - val_loss: 0.2582\n",
|
|
"Epoch 321/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9164 - loss: 0.1809 - val_accuracy: 0.8827 - val_loss: 0.2871\n",
|
|
"Epoch 322/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9112 - loss: 0.1941 - val_accuracy: 0.8955 - val_loss: 0.2687\n",
|
|
"Epoch 323/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9186 - loss: 0.1860 - val_accuracy: 0.8854 - val_loss: 0.2672\n",
|
|
"Epoch 324/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9093 - loss: 0.1874 - val_accuracy: 0.8863 - val_loss: 0.2694\n",
|
|
"Epoch 325/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9190 - loss: 0.1780 - val_accuracy: 0.8827 - val_loss: 0.2782\n",
|
|
"Epoch 326/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9173 - loss: 0.1872 - val_accuracy: 0.8937 - val_loss: 0.2651\n",
|
|
"Epoch 327/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9239 - loss: 0.1755 - val_accuracy: 0.8992 - val_loss: 0.2613\n",
|
|
"Epoch 328/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9154 - loss: 0.1847 - val_accuracy: 0.8818 - val_loss: 0.2890\n",
|
|
"Epoch 329/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9176 - loss: 0.1740 - val_accuracy: 0.8918 - val_loss: 0.2681\n",
|
|
"Epoch 330/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9130 - loss: 0.1836 - val_accuracy: 0.8900 - val_loss: 0.2656\n",
|
|
"Epoch 331/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9247 - loss: 0.1757 - val_accuracy: 0.8946 - val_loss: 0.2655\n",
|
|
"Epoch 332/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9216 - loss: 0.1791 - val_accuracy: 0.8928 - val_loss: 0.2607\n",
|
|
"Epoch 333/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9200 - loss: 0.1857 - val_accuracy: 0.8900 - val_loss: 0.2716\n",
|
|
"Epoch 334/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9154 - loss: 0.1951 - val_accuracy: 0.8882 - val_loss: 0.2673\n",
|
|
"Epoch 335/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9166 - loss: 0.1845 - val_accuracy: 0.8882 - val_loss: 0.2708\n",
|
|
"Epoch 336/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9187 - loss: 0.1796 - val_accuracy: 0.8909 - val_loss: 0.2647\n",
|
|
"Epoch 337/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9202 - loss: 0.1813 - val_accuracy: 0.8882 - val_loss: 0.2793\n",
|
|
"Epoch 338/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9106 - loss: 0.1875 - val_accuracy: 0.8900 - val_loss: 0.2738\n",
|
|
"Epoch 339/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9195 - loss: 0.1848 - val_accuracy: 0.8863 - val_loss: 0.2897\n",
|
|
"Epoch 340/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9179 - loss: 0.1860 - val_accuracy: 0.8928 - val_loss: 0.2644\n",
|
|
"Epoch 341/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9189 - loss: 0.1770 - val_accuracy: 0.8909 - val_loss: 0.2730\n",
|
|
"Epoch 342/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9190 - loss: 0.1915 - val_accuracy: 0.8937 - val_loss: 0.2692\n",
|
|
"Epoch 343/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9202 - loss: 0.1779 - val_accuracy: 0.8918 - val_loss: 0.2676\n",
|
|
"Epoch 344/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9300 - loss: 0.1715 - val_accuracy: 0.8781 - val_loss: 0.3034\n",
|
|
"Epoch 345/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9123 - loss: 0.1927 - val_accuracy: 0.8955 - val_loss: 0.2652\n",
|
|
"Epoch 346/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9237 - loss: 0.1709 - val_accuracy: 0.8937 - val_loss: 0.2662\n",
|
|
"Epoch 347/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9265 - loss: 0.1722 - val_accuracy: 0.8937 - val_loss: 0.2603\n",
|
|
"Epoch 348/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9167 - loss: 0.1753 - val_accuracy: 0.8928 - val_loss: 0.2621\n",
|
|
"Epoch 349/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9225 - loss: 0.1701 - val_accuracy: 0.8763 - val_loss: 0.3072\n",
|
|
"Epoch 350/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9182 - loss: 0.1874 - val_accuracy: 0.8836 - val_loss: 0.2894\n",
|
|
"Epoch 351/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9082 - loss: 0.1998 - val_accuracy: 0.8937 - val_loss: 0.2686\n",
|
|
"Epoch 352/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9193 - loss: 0.1738 - val_accuracy: 0.8827 - val_loss: 0.2784\n",
|
|
"Epoch 353/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9261 - loss: 0.1719 - val_accuracy: 0.8818 - val_loss: 0.2777\n",
|
|
"Epoch 354/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9273 - loss: 0.1744 - val_accuracy: 0.8873 - val_loss: 0.2646\n",
|
|
"Epoch 355/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9158 - loss: 0.1903 - val_accuracy: 0.8918 - val_loss: 0.2658\n",
|
|
"Epoch 356/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9189 - loss: 0.1761 - val_accuracy: 0.8937 - val_loss: 0.2669\n",
|
|
"Epoch 357/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9202 - loss: 0.1738 - val_accuracy: 0.8983 - val_loss: 0.2662\n",
|
|
"Epoch 358/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9179 - loss: 0.1865 - val_accuracy: 0.8900 - val_loss: 0.2667\n",
|
|
"Epoch 359/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9076 - loss: 0.1909 - val_accuracy: 0.8873 - val_loss: 0.2774\n",
|
|
"Epoch 360/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9116 - loss: 0.2014 - val_accuracy: 0.8753 - val_loss: 0.2935\n",
|
|
"Epoch 361/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9174 - loss: 0.1836 - val_accuracy: 0.8863 - val_loss: 0.2735\n",
|
|
"Epoch 362/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9198 - loss: 0.1891 - val_accuracy: 0.8818 - val_loss: 0.2900\n",
|
|
"Epoch 363/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9218 - loss: 0.1801 - val_accuracy: 0.8918 - val_loss: 0.2927\n",
|
|
"Epoch 364/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9143 - loss: 0.1837 - val_accuracy: 0.8882 - val_loss: 0.2793\n",
|
|
"Epoch 365/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9025 - loss: 0.1954 - val_accuracy: 0.8946 - val_loss: 0.2636\n",
|
|
"Epoch 366/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9254 - loss: 0.1699 - val_accuracy: 0.8753 - val_loss: 0.3099\n",
|
|
"Epoch 367/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9123 - loss: 0.1921 - val_accuracy: 0.8873 - val_loss: 0.2853\n",
|
|
"Epoch 368/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9119 - loss: 0.1952 - val_accuracy: 0.8928 - val_loss: 0.2648\n",
|
|
"Epoch 369/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9132 - loss: 0.1804 - val_accuracy: 0.8946 - val_loss: 0.2622\n",
|
|
"Epoch 370/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9169 - loss: 0.1834 - val_accuracy: 0.8909 - val_loss: 0.2687\n",
|
|
"Epoch 371/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9277 - loss: 0.1642 - val_accuracy: 0.8891 - val_loss: 0.2620\n",
|
|
"Epoch 372/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9187 - loss: 0.1736 - val_accuracy: 0.8873 - val_loss: 0.2770\n",
|
|
"Epoch 373/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9151 - loss: 0.1849 - val_accuracy: 0.8854 - val_loss: 0.2725\n",
|
|
"Epoch 374/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9183 - loss: 0.1787 - val_accuracy: 0.8818 - val_loss: 0.2777\n",
|
|
"Epoch 375/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9174 - loss: 0.1827 - val_accuracy: 0.8863 - val_loss: 0.2708\n",
|
|
"Epoch 376/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9164 - loss: 0.1845 - val_accuracy: 0.8863 - val_loss: 0.2676\n",
|
|
"Epoch 377/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9265 - loss: 0.1642 - val_accuracy: 0.8964 - val_loss: 0.2635\n",
|
|
"Epoch 378/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9253 - loss: 0.1659 - val_accuracy: 0.8928 - val_loss: 0.2666\n",
|
|
"Epoch 379/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9205 - loss: 0.1747 - val_accuracy: 0.8900 - val_loss: 0.2674\n",
|
|
"Epoch 380/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9231 - loss: 0.1700 - val_accuracy: 0.8964 - val_loss: 0.2746\n",
|
|
"Epoch 381/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9160 - loss: 0.1855 - val_accuracy: 0.8900 - val_loss: 0.2591\n",
|
|
"Epoch 382/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9164 - loss: 0.1820 - val_accuracy: 0.8827 - val_loss: 0.2763\n",
|
|
"Epoch 383/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9259 - loss: 0.1793 - val_accuracy: 0.8937 - val_loss: 0.2619\n",
|
|
"Epoch 384/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9253 - loss: 0.1805 - val_accuracy: 0.9001 - val_loss: 0.2604\n",
|
|
"Epoch 385/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9160 - loss: 0.1796 - val_accuracy: 0.8983 - val_loss: 0.2756\n",
|
|
"Epoch 386/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9225 - loss: 0.1738 - val_accuracy: 0.8928 - val_loss: 0.2662\n",
|
|
"Epoch 387/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9203 - loss: 0.1715 - val_accuracy: 0.8808 - val_loss: 0.2755\n",
|
|
"Epoch 388/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9088 - loss: 0.2025 - val_accuracy: 0.8873 - val_loss: 0.2770\n",
|
|
"Epoch 389/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9225 - loss: 0.1776 - val_accuracy: 0.8946 - val_loss: 0.2594\n",
|
|
"Epoch 390/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9279 - loss: 0.1661 - val_accuracy: 0.8790 - val_loss: 0.2996\n",
|
|
"Epoch 391/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9174 - loss: 0.1845 - val_accuracy: 0.8818 - val_loss: 0.2801\n",
|
|
"Epoch 392/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9228 - loss: 0.1632 - val_accuracy: 0.8955 - val_loss: 0.2709\n",
|
|
"Epoch 393/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9250 - loss: 0.1640 - val_accuracy: 0.8955 - val_loss: 0.2722\n",
|
|
"Epoch 394/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9199 - loss: 0.1733 - val_accuracy: 0.8937 - val_loss: 0.2641\n",
|
|
"Epoch 395/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9196 - loss: 0.1717 - val_accuracy: 0.8662 - val_loss: 0.3393\n",
|
|
"Epoch 396/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9066 - loss: 0.2030 - val_accuracy: 0.8854 - val_loss: 0.2809\n",
|
|
"Epoch 397/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9153 - loss: 0.1896 - val_accuracy: 0.8937 - val_loss: 0.2790\n",
|
|
"Epoch 398/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9146 - loss: 0.1798 - val_accuracy: 0.8937 - val_loss: 0.2630\n",
|
|
"Epoch 399/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9218 - loss: 0.1757 - val_accuracy: 0.8873 - val_loss: 0.2754\n",
|
|
"Epoch 400/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9131 - loss: 0.1857 - val_accuracy: 0.8928 - val_loss: 0.2782\n",
|
|
"Epoch 401/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9239 - loss: 0.1722 - val_accuracy: 0.8909 - val_loss: 0.2667\n",
|
|
"Epoch 402/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9212 - loss: 0.1724 - val_accuracy: 0.8827 - val_loss: 0.2883\n",
|
|
"Epoch 403/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9217 - loss: 0.1683 - val_accuracy: 0.8845 - val_loss: 0.2727\n",
|
|
"Epoch 404/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9225 - loss: 0.1781 - val_accuracy: 0.8909 - val_loss: 0.2670\n",
|
|
"Epoch 405/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9222 - loss: 0.1760 - val_accuracy: 0.8891 - val_loss: 0.2797\n",
|
|
"Epoch 406/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9269 - loss: 0.1662 - val_accuracy: 0.8634 - val_loss: 0.3358\n",
|
|
"Epoch 407/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9077 - loss: 0.2009 - val_accuracy: 0.8781 - val_loss: 0.3029\n",
|
|
"Epoch 408/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9223 - loss: 0.1699 - val_accuracy: 0.8937 - val_loss: 0.2715\n",
|
|
"Epoch 409/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9200 - loss: 0.1767 - val_accuracy: 0.8836 - val_loss: 0.2745\n",
|
|
"Epoch 410/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9154 - loss: 0.1819 - val_accuracy: 0.8946 - val_loss: 0.2694\n",
|
|
"Epoch 411/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9169 - loss: 0.1761 - val_accuracy: 0.8818 - val_loss: 0.2958\n",
|
|
"Epoch 412/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9167 - loss: 0.1773 - val_accuracy: 0.8983 - val_loss: 0.2691\n",
|
|
"Epoch 413/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9246 - loss: 0.1637 - val_accuracy: 0.8836 - val_loss: 0.2742\n",
|
|
"Epoch 414/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9187 - loss: 0.1806 - val_accuracy: 0.8900 - val_loss: 0.2727\n",
|
|
"Epoch 415/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9246 - loss: 0.1657 - val_accuracy: 0.8845 - val_loss: 0.2809\n",
|
|
"Epoch 416/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9340 - loss: 0.1608 - val_accuracy: 0.8909 - val_loss: 0.2727\n",
|
|
"Epoch 417/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9211 - loss: 0.1746 - val_accuracy: 0.8937 - val_loss: 0.2638\n",
|
|
"Epoch 418/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9232 - loss: 0.1713 - val_accuracy: 0.8882 - val_loss: 0.2870\n",
|
|
"Epoch 419/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9218 - loss: 0.1775 - val_accuracy: 0.8799 - val_loss: 0.2932\n",
|
|
"Epoch 420/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9025 - loss: 0.2156 - val_accuracy: 0.8983 - val_loss: 0.2720\n",
|
|
"Epoch 421/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9202 - loss: 0.1733 - val_accuracy: 0.8854 - val_loss: 0.2812\n",
|
|
"Epoch 422/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9222 - loss: 0.1702 - val_accuracy: 0.8790 - val_loss: 0.2967\n",
|
|
"Epoch 423/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9113 - loss: 0.1816 - val_accuracy: 0.8928 - val_loss: 0.2691\n",
|
|
"Epoch 424/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9260 - loss: 0.1752 - val_accuracy: 0.8891 - val_loss: 0.2713\n",
|
|
"Epoch 425/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9302 - loss: 0.1649 - val_accuracy: 0.8634 - val_loss: 0.3383\n",
|
|
"Epoch 426/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9172 - loss: 0.1882 - val_accuracy: 0.8763 - val_loss: 0.2788\n",
|
|
"Epoch 427/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9304 - loss: 0.1692 - val_accuracy: 0.8873 - val_loss: 0.2817\n",
|
|
"Epoch 428/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9226 - loss: 0.1709 - val_accuracy: 0.8946 - val_loss: 0.2686\n",
|
|
"Epoch 429/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9233 - loss: 0.1663 - val_accuracy: 0.8863 - val_loss: 0.2620\n",
|
|
"Epoch 430/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9272 - loss: 0.1653 - val_accuracy: 0.8964 - val_loss: 0.2716\n",
|
|
"Epoch 431/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9283 - loss: 0.1599 - val_accuracy: 0.8735 - val_loss: 0.2948\n",
|
|
"Epoch 432/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9316 - loss: 0.1698 - val_accuracy: 0.8863 - val_loss: 0.2808\n",
|
|
"Epoch 433/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9214 - loss: 0.1693 - val_accuracy: 0.8882 - val_loss: 0.2770\n",
|
|
"Epoch 434/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9220 - loss: 0.1660 - val_accuracy: 0.8836 - val_loss: 0.2670\n",
|
|
"Epoch 435/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9161 - loss: 0.1801 - val_accuracy: 0.8900 - val_loss: 0.2652\n",
|
|
"Epoch 436/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9341 - loss: 0.1580 - val_accuracy: 0.8983 - val_loss: 0.2774\n",
|
|
"Epoch 437/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9266 - loss: 0.1750 - val_accuracy: 0.8854 - val_loss: 0.2837\n",
|
|
"Epoch 438/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9194 - loss: 0.1714 - val_accuracy: 0.8891 - val_loss: 0.2694\n",
|
|
"Epoch 439/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9262 - loss: 0.1681 - val_accuracy: 0.8937 - val_loss: 0.2700\n",
|
|
"Epoch 440/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9222 - loss: 0.1728 - val_accuracy: 0.8909 - val_loss: 0.2720\n",
|
|
"Epoch 441/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9119 - loss: 0.1870 - val_accuracy: 0.8790 - val_loss: 0.2962\n",
|
|
"Epoch 442/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9176 - loss: 0.1722 - val_accuracy: 0.8918 - val_loss: 0.2772\n",
|
|
"Epoch 443/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9194 - loss: 0.1782 - val_accuracy: 0.8808 - val_loss: 0.2941\n",
|
|
"Epoch 444/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9185 - loss: 0.1818 - val_accuracy: 0.8918 - val_loss: 0.2755\n",
|
|
"Epoch 445/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9263 - loss: 0.1628 - val_accuracy: 0.8983 - val_loss: 0.2670\n",
|
|
"Epoch 446/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9311 - loss: 0.1581 - val_accuracy: 0.8955 - val_loss: 0.2647\n",
|
|
"Epoch 447/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9273 - loss: 0.1581 - val_accuracy: 0.9001 - val_loss: 0.2663\n",
|
|
"Epoch 448/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9210 - loss: 0.1741 - val_accuracy: 0.8854 - val_loss: 0.2822\n",
|
|
"Epoch 449/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9183 - loss: 0.1766 - val_accuracy: 0.8827 - val_loss: 0.2773\n",
|
|
"Epoch 450/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9233 - loss: 0.1657 - val_accuracy: 0.8891 - val_loss: 0.2788\n",
|
|
"Epoch 451/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9241 - loss: 0.1615 - val_accuracy: 0.8937 - val_loss: 0.2714\n",
|
|
"Epoch 452/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9242 - loss: 0.1706 - val_accuracy: 0.8891 - val_loss: 0.2748\n",
|
|
"Epoch 453/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9190 - loss: 0.1798 - val_accuracy: 0.8900 - val_loss: 0.2927\n",
|
|
"Epoch 454/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9177 - loss: 0.1718 - val_accuracy: 0.8790 - val_loss: 0.2897\n",
|
|
"Epoch 455/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9217 - loss: 0.1685 - val_accuracy: 0.8818 - val_loss: 0.2676\n",
|
|
"Epoch 456/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9187 - loss: 0.1789 - val_accuracy: 0.8863 - val_loss: 0.2734\n",
|
|
"Epoch 457/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9271 - loss: 0.1665 - val_accuracy: 0.8964 - val_loss: 0.2666\n",
|
|
"Epoch 458/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9245 - loss: 0.1619 - val_accuracy: 0.8781 - val_loss: 0.2971\n",
|
|
"Epoch 459/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9298 - loss: 0.1634 - val_accuracy: 0.8882 - val_loss: 0.2706\n",
|
|
"Epoch 460/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9208 - loss: 0.1681 - val_accuracy: 0.8973 - val_loss: 0.2758\n",
|
|
"Epoch 461/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9254 - loss: 0.1778 - val_accuracy: 0.8808 - val_loss: 0.2834\n",
|
|
"Epoch 462/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9203 - loss: 0.1705 - val_accuracy: 0.8799 - val_loss: 0.2810\n",
|
|
"Epoch 463/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9158 - loss: 0.1889 - val_accuracy: 0.8873 - val_loss: 0.2778\n",
|
|
"Epoch 464/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9314 - loss: 0.1521 - val_accuracy: 0.8854 - val_loss: 0.2727\n",
|
|
"Epoch 465/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9310 - loss: 0.1634 - val_accuracy: 0.8909 - val_loss: 0.2793\n",
|
|
"Epoch 466/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9230 - loss: 0.1724 - val_accuracy: 0.8845 - val_loss: 0.2714\n",
|
|
"Epoch 467/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9257 - loss: 0.1646 - val_accuracy: 0.8735 - val_loss: 0.3140\n",
|
|
"Epoch 468/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9260 - loss: 0.1709 - val_accuracy: 0.8827 - val_loss: 0.2801\n",
|
|
"Epoch 469/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9238 - loss: 0.1675 - val_accuracy: 0.8854 - val_loss: 0.2995\n",
|
|
"Epoch 470/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9271 - loss: 0.1668 - val_accuracy: 0.8643 - val_loss: 0.3328\n",
|
|
"Epoch 471/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9149 - loss: 0.1882 - val_accuracy: 0.8891 - val_loss: 0.2900\n",
|
|
"Epoch 472/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9240 - loss: 0.1747 - val_accuracy: 0.8946 - val_loss: 0.2960\n",
|
|
"Epoch 473/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9209 - loss: 0.1677 - val_accuracy: 0.8955 - val_loss: 0.2858\n",
|
|
"Epoch 474/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9288 - loss: 0.1574 - val_accuracy: 0.8836 - val_loss: 0.2890\n",
|
|
"Epoch 475/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9158 - loss: 0.1795 - val_accuracy: 0.8918 - val_loss: 0.2735\n",
|
|
"Epoch 476/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9274 - loss: 0.1673 - val_accuracy: 0.8891 - val_loss: 0.2705\n",
|
|
"Epoch 477/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9268 - loss: 0.1714 - val_accuracy: 0.8937 - val_loss: 0.2735\n",
|
|
"Epoch 478/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9223 - loss: 0.1696 - val_accuracy: 0.8918 - val_loss: 0.2685\n",
|
|
"Epoch 479/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9349 - loss: 0.1565 - val_accuracy: 0.8900 - val_loss: 0.2847\n",
|
|
"Epoch 480/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9264 - loss: 0.1638 - val_accuracy: 0.8808 - val_loss: 0.2734\n",
|
|
"Epoch 481/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9271 - loss: 0.1614 - val_accuracy: 0.8873 - val_loss: 0.2818\n",
|
|
"Epoch 482/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9164 - loss: 0.1768 - val_accuracy: 0.8863 - val_loss: 0.2902\n",
|
|
"Epoch 483/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9364 - loss: 0.1453 - val_accuracy: 0.8937 - val_loss: 0.2852\n",
|
|
"Epoch 484/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9181 - loss: 0.1732 - val_accuracy: 0.8946 - val_loss: 0.2641\n",
|
|
"Epoch 485/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9275 - loss: 0.1635 - val_accuracy: 0.8854 - val_loss: 0.2916\n",
|
|
"Epoch 486/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9213 - loss: 0.1747 - val_accuracy: 0.8799 - val_loss: 0.3200\n",
|
|
"Epoch 487/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9164 - loss: 0.1699 - val_accuracy: 0.8882 - val_loss: 0.2738\n",
|
|
"Epoch 488/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9317 - loss: 0.1636 - val_accuracy: 0.8863 - val_loss: 0.2799\n",
|
|
"Epoch 489/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9215 - loss: 0.1669 - val_accuracy: 0.8928 - val_loss: 0.2770\n",
|
|
"Epoch 490/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9192 - loss: 0.1732 - val_accuracy: 0.8873 - val_loss: 0.2826\n",
|
|
"Epoch 491/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9248 - loss: 0.1677 - val_accuracy: 0.8799 - val_loss: 0.2793\n",
|
|
"Epoch 492/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9266 - loss: 0.1582 - val_accuracy: 0.8818 - val_loss: 0.2843\n",
|
|
"Epoch 493/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9177 - loss: 0.1823 - val_accuracy: 0.8863 - val_loss: 0.2772\n",
|
|
"Epoch 494/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9235 - loss: 0.1729 - val_accuracy: 0.8717 - val_loss: 0.2747\n",
|
|
"Epoch 495/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9257 - loss: 0.1711 - val_accuracy: 0.8781 - val_loss: 0.3104\n",
|
|
"Epoch 496/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9230 - loss: 0.1633 - val_accuracy: 0.8818 - val_loss: 0.2897\n",
|
|
"Epoch 497/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9263 - loss: 0.1640 - val_accuracy: 0.8735 - val_loss: 0.2944\n",
|
|
"Epoch 498/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9282 - loss: 0.1590 - val_accuracy: 0.8909 - val_loss: 0.2772\n",
|
|
"Epoch 499/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9251 - loss: 0.1611 - val_accuracy: 0.8873 - val_loss: 0.2931\n",
|
|
"Epoch 500/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9259 - loss: 0.1632 - val_accuracy: 0.8918 - val_loss: 0.2766\n",
|
|
"Epoch 501/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9228 - loss: 0.1631 - val_accuracy: 0.8882 - val_loss: 0.2741\n",
|
|
"Epoch 502/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9266 - loss: 0.1606 - val_accuracy: 0.8781 - val_loss: 0.2770\n",
|
|
"Epoch 503/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9217 - loss: 0.1703 - val_accuracy: 0.8946 - val_loss: 0.2816\n",
|
|
"Epoch 504/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9271 - loss: 0.1706 - val_accuracy: 0.8937 - val_loss: 0.2726\n",
|
|
"Epoch 505/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9362 - loss: 0.1553 - val_accuracy: 0.8900 - val_loss: 0.2780\n",
|
|
"Epoch 506/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9290 - loss: 0.1646 - val_accuracy: 0.8863 - val_loss: 0.3070\n",
|
|
"Epoch 507/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9256 - loss: 0.1696 - val_accuracy: 0.8827 - val_loss: 0.2871\n",
|
|
"Epoch 508/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9272 - loss: 0.1526 - val_accuracy: 0.8882 - val_loss: 0.2747\n",
|
|
"Epoch 509/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9284 - loss: 0.1602 - val_accuracy: 0.8891 - val_loss: 0.2868\n",
|
|
"Epoch 510/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9367 - loss: 0.1571 - val_accuracy: 0.8891 - val_loss: 0.2827\n",
|
|
"Epoch 511/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9368 - loss: 0.1538 - val_accuracy: 0.8873 - val_loss: 0.2810\n",
|
|
"Epoch 512/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9132 - loss: 0.1806 - val_accuracy: 0.8900 - val_loss: 0.2780\n",
|
|
"Epoch 513/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9290 - loss: 0.1563 - val_accuracy: 0.8763 - val_loss: 0.2864\n",
|
|
"Epoch 514/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9337 - loss: 0.1545 - val_accuracy: 0.8946 - val_loss: 0.2681\n",
|
|
"Epoch 515/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9284 - loss: 0.1597 - val_accuracy: 0.8882 - val_loss: 0.3104\n",
|
|
"Epoch 516/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9246 - loss: 0.1679 - val_accuracy: 0.8827 - val_loss: 0.2827\n",
|
|
"Epoch 517/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9312 - loss: 0.1570 - val_accuracy: 0.8836 - val_loss: 0.3059\n",
|
|
"Epoch 518/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9310 - loss: 0.1530 - val_accuracy: 0.8845 - val_loss: 0.2879\n",
|
|
"Epoch 519/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9237 - loss: 0.1588 - val_accuracy: 0.8928 - val_loss: 0.2730\n",
|
|
"Epoch 520/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9310 - loss: 0.1605 - val_accuracy: 0.8918 - val_loss: 0.2883\n",
|
|
"Epoch 521/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9315 - loss: 0.1538 - val_accuracy: 0.8891 - val_loss: 0.2723\n",
|
|
"Epoch 522/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9340 - loss: 0.1479 - val_accuracy: 0.8818 - val_loss: 0.3009\n",
|
|
"Epoch 523/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9167 - loss: 0.1856 - val_accuracy: 0.8827 - val_loss: 0.2994\n",
|
|
"Epoch 524/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9296 - loss: 0.1632 - val_accuracy: 0.9019 - val_loss: 0.2692\n",
|
|
"Epoch 525/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9319 - loss: 0.1609 - val_accuracy: 0.8845 - val_loss: 0.2820\n",
|
|
"Epoch 526/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9338 - loss: 0.1531 - val_accuracy: 0.8818 - val_loss: 0.3103\n",
|
|
"Epoch 527/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9285 - loss: 0.1634 - val_accuracy: 0.8882 - val_loss: 0.2911\n",
|
|
"Epoch 528/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9205 - loss: 0.1673 - val_accuracy: 0.8891 - val_loss: 0.2849\n",
|
|
"Epoch 529/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9313 - loss: 0.1530 - val_accuracy: 0.8891 - val_loss: 0.2872\n",
|
|
"Epoch 530/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9277 - loss: 0.1636 - val_accuracy: 0.8900 - val_loss: 0.2914\n",
|
|
"Epoch 531/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9279 - loss: 0.1591 - val_accuracy: 0.8854 - val_loss: 0.3099\n",
|
|
"Epoch 532/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9273 - loss: 0.1593 - val_accuracy: 0.8900 - val_loss: 0.2793\n",
|
|
"Epoch 533/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9316 - loss: 0.1615 - val_accuracy: 0.8909 - val_loss: 0.2852\n",
|
|
"Epoch 534/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9212 - loss: 0.1643 - val_accuracy: 0.8873 - val_loss: 0.2975\n",
|
|
"Epoch 535/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9258 - loss: 0.1588 - val_accuracy: 0.8928 - val_loss: 0.2819\n",
|
|
"Epoch 536/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9287 - loss: 0.1605 - val_accuracy: 0.8845 - val_loss: 0.2799\n",
|
|
"Epoch 537/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9299 - loss: 0.1586 - val_accuracy: 0.8882 - val_loss: 0.2786\n",
|
|
"Epoch 538/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9333 - loss: 0.1617 - val_accuracy: 0.8900 - val_loss: 0.2765\n",
|
|
"Epoch 539/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9330 - loss: 0.1533 - val_accuracy: 0.8836 - val_loss: 0.2910\n",
|
|
"Epoch 540/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9340 - loss: 0.1475 - val_accuracy: 0.8882 - val_loss: 0.2860\n",
|
|
"Epoch 541/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9292 - loss: 0.1558 - val_accuracy: 0.8854 - val_loss: 0.2797\n",
|
|
"Epoch 542/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9323 - loss: 0.1532 - val_accuracy: 0.8900 - val_loss: 0.2856\n",
|
|
"Epoch 543/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9266 - loss: 0.1613 - val_accuracy: 0.8928 - val_loss: 0.2961\n",
|
|
"Epoch 544/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9303 - loss: 0.1543 - val_accuracy: 0.8827 - val_loss: 0.2922\n",
|
|
"Epoch 545/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9296 - loss: 0.1534 - val_accuracy: 0.8900 - val_loss: 0.2846\n",
|
|
"Epoch 546/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9258 - loss: 0.1573 - val_accuracy: 0.8863 - val_loss: 0.2995\n",
|
|
"Epoch 547/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9339 - loss: 0.1533 - val_accuracy: 0.8763 - val_loss: 0.3194\n",
|
|
"Epoch 548/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9250 - loss: 0.1712 - val_accuracy: 0.8818 - val_loss: 0.2984\n",
|
|
"Epoch 549/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9253 - loss: 0.1650 - val_accuracy: 0.8753 - val_loss: 0.3172\n",
|
|
"Epoch 550/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9293 - loss: 0.1519 - val_accuracy: 0.8726 - val_loss: 0.3133\n",
|
|
"Epoch 551/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9297 - loss: 0.1517 - val_accuracy: 0.8873 - val_loss: 0.2847\n",
|
|
"Epoch 552/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9327 - loss: 0.1543 - val_accuracy: 0.8873 - val_loss: 0.2824\n",
|
|
"Epoch 553/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9322 - loss: 0.1536 - val_accuracy: 0.8863 - val_loss: 0.2951\n",
|
|
"Epoch 554/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9324 - loss: 0.1560 - val_accuracy: 0.8836 - val_loss: 0.2676\n",
|
|
"Epoch 555/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9298 - loss: 0.1574 - val_accuracy: 0.8845 - val_loss: 0.2925\n",
|
|
"Epoch 556/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9340 - loss: 0.1603 - val_accuracy: 0.8909 - val_loss: 0.2850\n",
|
|
"Epoch 557/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9393 - loss: 0.1435 - val_accuracy: 0.8928 - val_loss: 0.2741\n",
|
|
"Epoch 558/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9286 - loss: 0.1555 - val_accuracy: 0.8808 - val_loss: 0.3057\n",
|
|
"Epoch 559/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9329 - loss: 0.1522 - val_accuracy: 0.8863 - val_loss: 0.2996\n",
|
|
"Epoch 560/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9410 - loss: 0.1477 - val_accuracy: 0.8854 - val_loss: 0.2960\n",
|
|
"Epoch 561/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9315 - loss: 0.1535 - val_accuracy: 0.8928 - val_loss: 0.2884\n",
|
|
"Epoch 562/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9379 - loss: 0.1481 - val_accuracy: 0.8891 - val_loss: 0.2836\n",
|
|
"Epoch 563/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9296 - loss: 0.1558 - val_accuracy: 0.8900 - val_loss: 0.2872\n",
|
|
"Epoch 564/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9336 - loss: 0.1477 - val_accuracy: 0.8854 - val_loss: 0.2841\n",
|
|
"Epoch 565/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9293 - loss: 0.1517 - val_accuracy: 0.8918 - val_loss: 0.2878\n",
|
|
"Epoch 566/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9411 - loss: 0.1399 - val_accuracy: 0.8891 - val_loss: 0.2959\n",
|
|
"Epoch 567/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9372 - loss: 0.1555 - val_accuracy: 0.8735 - val_loss: 0.3099\n",
|
|
"Epoch 568/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9357 - loss: 0.1455 - val_accuracy: 0.8918 - val_loss: 0.2857\n",
|
|
"Epoch 569/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9246 - loss: 0.1620 - val_accuracy: 0.8799 - val_loss: 0.2721\n",
|
|
"Epoch 570/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9296 - loss: 0.1587 - val_accuracy: 0.8662 - val_loss: 0.3653\n",
|
|
"Epoch 571/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9188 - loss: 0.1709 - val_accuracy: 0.8827 - val_loss: 0.3067\n",
|
|
"Epoch 572/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9355 - loss: 0.1392 - val_accuracy: 0.8808 - val_loss: 0.2815\n",
|
|
"Epoch 573/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9341 - loss: 0.1541 - val_accuracy: 0.8863 - val_loss: 0.3098\n",
|
|
"Epoch 574/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9323 - loss: 0.1502 - val_accuracy: 0.8873 - val_loss: 0.2869\n",
|
|
"Epoch 575/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9326 - loss: 0.1566 - val_accuracy: 0.8918 - val_loss: 0.2872\n",
|
|
"Epoch 576/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9333 - loss: 0.1461 - val_accuracy: 0.8964 - val_loss: 0.2912\n",
|
|
"Epoch 577/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9389 - loss: 0.1479 - val_accuracy: 0.8836 - val_loss: 0.3026\n",
|
|
"Epoch 578/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9277 - loss: 0.1577 - val_accuracy: 0.8836 - val_loss: 0.2852\n",
|
|
"Epoch 579/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9296 - loss: 0.1598 - val_accuracy: 0.8891 - val_loss: 0.2744\n",
|
|
"Epoch 580/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9209 - loss: 0.1721 - val_accuracy: 0.8891 - val_loss: 0.2855\n",
|
|
"Epoch 581/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9375 - loss: 0.1456 - val_accuracy: 0.8836 - val_loss: 0.3053\n",
|
|
"Epoch 582/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9392 - loss: 0.1429 - val_accuracy: 0.8946 - val_loss: 0.2817\n",
|
|
"Epoch 583/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9333 - loss: 0.1465 - val_accuracy: 0.8964 - val_loss: 0.2887\n",
|
|
"Epoch 584/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9335 - loss: 0.1458 - val_accuracy: 0.8753 - val_loss: 0.2920\n",
|
|
"Epoch 585/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9368 - loss: 0.1407 - val_accuracy: 0.8882 - val_loss: 0.3125\n",
|
|
"Epoch 586/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9344 - loss: 0.1492 - val_accuracy: 0.8799 - val_loss: 0.2928\n",
|
|
"Epoch 587/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9347 - loss: 0.1453 - val_accuracy: 0.8863 - val_loss: 0.2988\n",
|
|
"Epoch 588/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9352 - loss: 0.1473 - val_accuracy: 0.8808 - val_loss: 0.2932\n",
|
|
"Epoch 589/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9334 - loss: 0.1487 - val_accuracy: 0.8799 - val_loss: 0.2879\n",
|
|
"Epoch 590/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9256 - loss: 0.1658 - val_accuracy: 0.8799 - val_loss: 0.2889\n",
|
|
"Epoch 591/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9407 - loss: 0.1307 - val_accuracy: 0.8873 - val_loss: 0.2815\n",
|
|
"Epoch 592/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9250 - loss: 0.1556 - val_accuracy: 0.8955 - val_loss: 0.2813\n",
|
|
"Epoch 593/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9298 - loss: 0.1464 - val_accuracy: 0.8845 - val_loss: 0.2893\n",
|
|
"Epoch 594/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9349 - loss: 0.1487 - val_accuracy: 0.8900 - val_loss: 0.3035\n",
|
|
"Epoch 595/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9361 - loss: 0.1515 - val_accuracy: 0.8845 - val_loss: 0.2872\n",
|
|
"Epoch 596/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9360 - loss: 0.1499 - val_accuracy: 0.8891 - val_loss: 0.3052\n",
|
|
"Epoch 597/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9332 - loss: 0.1500 - val_accuracy: 0.8928 - val_loss: 0.2972\n",
|
|
"Epoch 598/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9314 - loss: 0.1533 - val_accuracy: 0.8882 - val_loss: 0.2906\n",
|
|
"Epoch 599/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9436 - loss: 0.1373 - val_accuracy: 0.8863 - val_loss: 0.2943\n",
|
|
"Epoch 600/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9380 - loss: 0.1416 - val_accuracy: 0.8790 - val_loss: 0.2876\n",
|
|
"Epoch 601/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9255 - loss: 0.1662 - val_accuracy: 0.8863 - val_loss: 0.3211\n",
|
|
"Epoch 602/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9398 - loss: 0.1368 - val_accuracy: 0.8836 - val_loss: 0.2927\n",
|
|
"Epoch 603/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9364 - loss: 0.1411 - val_accuracy: 0.8836 - val_loss: 0.2995\n",
|
|
"Epoch 604/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9345 - loss: 0.1413 - val_accuracy: 0.8873 - val_loss: 0.3031\n",
|
|
"Epoch 605/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9304 - loss: 0.1546 - val_accuracy: 0.8891 - val_loss: 0.2863\n",
|
|
"Epoch 606/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9363 - loss: 0.1395 - val_accuracy: 0.8845 - val_loss: 0.3053\n",
|
|
"Epoch 607/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9348 - loss: 0.1397 - val_accuracy: 0.8818 - val_loss: 0.2859\n",
|
|
"Epoch 608/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9305 - loss: 0.1534 - val_accuracy: 0.8900 - val_loss: 0.2851\n",
|
|
"Epoch 609/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9327 - loss: 0.1485 - val_accuracy: 0.8836 - val_loss: 0.2880\n",
|
|
"Epoch 610/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9403 - loss: 0.1331 - val_accuracy: 0.8763 - val_loss: 0.3202\n",
|
|
"Epoch 611/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9290 - loss: 0.1565 - val_accuracy: 0.8790 - val_loss: 0.2885\n",
|
|
"Epoch 612/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9291 - loss: 0.1601 - val_accuracy: 0.8845 - val_loss: 0.2901\n",
|
|
"Epoch 613/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9308 - loss: 0.1520 - val_accuracy: 0.8873 - val_loss: 0.2849\n",
|
|
"Epoch 614/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9373 - loss: 0.1397 - val_accuracy: 0.8818 - val_loss: 0.3000\n",
|
|
"Epoch 615/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9359 - loss: 0.1421 - val_accuracy: 0.8753 - val_loss: 0.2919\n",
|
|
"Epoch 616/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9428 - loss: 0.1386 - val_accuracy: 0.8873 - val_loss: 0.2903\n",
|
|
"Epoch 617/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9340 - loss: 0.1425 - val_accuracy: 0.8873 - val_loss: 0.3149\n",
|
|
"Epoch 618/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9317 - loss: 0.1607 - val_accuracy: 0.8818 - val_loss: 0.3069\n",
|
|
"Epoch 619/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9273 - loss: 0.1570 - val_accuracy: 0.8900 - val_loss: 0.2999\n",
|
|
"Epoch 620/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9363 - loss: 0.1342 - val_accuracy: 0.8863 - val_loss: 0.3042\n",
|
|
"Epoch 621/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9354 - loss: 0.1394 - val_accuracy: 0.8882 - val_loss: 0.2950\n",
|
|
"Epoch 622/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9410 - loss: 0.1393 - val_accuracy: 0.8836 - val_loss: 0.2996\n",
|
|
"Epoch 623/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9336 - loss: 0.1501 - val_accuracy: 0.8836 - val_loss: 0.2993\n",
|
|
"Epoch 624/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9375 - loss: 0.1366 - val_accuracy: 0.8928 - val_loss: 0.2911\n",
|
|
"Epoch 625/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9323 - loss: 0.1394 - val_accuracy: 0.8827 - val_loss: 0.2924\n",
|
|
"Epoch 626/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9417 - loss: 0.1460 - val_accuracy: 0.8772 - val_loss: 0.3091\n",
|
|
"Epoch 627/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9365 - loss: 0.1484 - val_accuracy: 0.8717 - val_loss: 0.3624\n",
|
|
"Epoch 628/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9245 - loss: 0.1601 - val_accuracy: 0.8909 - val_loss: 0.2882\n",
|
|
"Epoch 629/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9362 - loss: 0.1422 - val_accuracy: 0.8836 - val_loss: 0.3317\n",
|
|
"Epoch 630/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9350 - loss: 0.1428 - val_accuracy: 0.8772 - val_loss: 0.3202\n",
|
|
"Epoch 631/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9379 - loss: 0.1369 - val_accuracy: 0.8863 - val_loss: 0.3095\n",
|
|
"Epoch 632/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9418 - loss: 0.1344 - val_accuracy: 0.8726 - val_loss: 0.3360\n",
|
|
"Epoch 633/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9350 - loss: 0.1567 - val_accuracy: 0.8891 - val_loss: 0.3001\n",
|
|
"Epoch 634/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9421 - loss: 0.1406 - val_accuracy: 0.8708 - val_loss: 0.3126\n",
|
|
"Epoch 635/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9336 - loss: 0.1387 - val_accuracy: 0.8726 - val_loss: 0.3712\n",
|
|
"Epoch 636/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9316 - loss: 0.1502 - val_accuracy: 0.8790 - val_loss: 0.3169\n",
|
|
"Epoch 637/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9370 - loss: 0.1279 - val_accuracy: 0.8763 - val_loss: 0.3077\n",
|
|
"Epoch 638/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9378 - loss: 0.1419 - val_accuracy: 0.8827 - val_loss: 0.3079\n",
|
|
"Epoch 639/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9358 - loss: 0.1377 - val_accuracy: 0.8781 - val_loss: 0.3154\n",
|
|
"Epoch 640/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9324 - loss: 0.1461 - val_accuracy: 0.8882 - val_loss: 0.2976\n",
|
|
"Epoch 641/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9309 - loss: 0.1492 - val_accuracy: 0.8882 - val_loss: 0.3215\n",
|
|
"Epoch 642/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9309 - loss: 0.1490 - val_accuracy: 0.8799 - val_loss: 0.3067\n",
|
|
"Epoch 643/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9519 - loss: 0.1291 - val_accuracy: 0.8818 - val_loss: 0.3128\n",
|
|
"Epoch 644/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9218 - loss: 0.1600 - val_accuracy: 0.8882 - val_loss: 0.3101\n",
|
|
"Epoch 645/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9386 - loss: 0.1365 - val_accuracy: 0.8790 - val_loss: 0.2885\n",
|
|
"Epoch 646/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9374 - loss: 0.1374 - val_accuracy: 0.8863 - val_loss: 0.2979\n",
|
|
"Epoch 647/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9432 - loss: 0.1313 - val_accuracy: 0.8891 - val_loss: 0.3047\n",
|
|
"Epoch 648/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9412 - loss: 0.1387 - val_accuracy: 0.8689 - val_loss: 0.3361\n",
|
|
"Epoch 649/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9333 - loss: 0.1386 - val_accuracy: 0.8772 - val_loss: 0.3070\n",
|
|
"Epoch 650/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9343 - loss: 0.1473 - val_accuracy: 0.8863 - val_loss: 0.3214\n",
|
|
"Epoch 651/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9295 - loss: 0.1515 - val_accuracy: 0.8882 - val_loss: 0.2925\n",
|
|
"Epoch 652/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9381 - loss: 0.1304 - val_accuracy: 0.8918 - val_loss: 0.2918\n",
|
|
"Epoch 653/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9415 - loss: 0.1285 - val_accuracy: 0.8900 - val_loss: 0.3128\n",
|
|
"Epoch 654/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9306 - loss: 0.1431 - val_accuracy: 0.8900 - val_loss: 0.2896\n",
|
|
"Epoch 655/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9420 - loss: 0.1375 - val_accuracy: 0.8928 - val_loss: 0.2964\n",
|
|
"Epoch 656/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9386 - loss: 0.1367 - val_accuracy: 0.8854 - val_loss: 0.2862\n",
|
|
"Epoch 657/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9348 - loss: 0.1439 - val_accuracy: 0.8900 - val_loss: 0.3327\n",
|
|
"Epoch 658/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9264 - loss: 0.1585 - val_accuracy: 0.8882 - val_loss: 0.3002\n",
|
|
"Epoch 659/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9318 - loss: 0.1437 - val_accuracy: 0.8873 - val_loss: 0.2985\n",
|
|
"Epoch 660/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9407 - loss: 0.1364 - val_accuracy: 0.8836 - val_loss: 0.2986\n",
|
|
"Epoch 661/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9361 - loss: 0.1370 - val_accuracy: 0.8845 - val_loss: 0.3029\n",
|
|
"Epoch 662/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9304 - loss: 0.1414 - val_accuracy: 0.8808 - val_loss: 0.2986\n",
|
|
"Epoch 663/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9305 - loss: 0.1486 - val_accuracy: 0.8854 - val_loss: 0.3053\n",
|
|
"Epoch 664/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9373 - loss: 0.1388 - val_accuracy: 0.8808 - val_loss: 0.3104\n",
|
|
"Epoch 665/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9307 - loss: 0.1464 - val_accuracy: 0.8845 - val_loss: 0.3004\n",
|
|
"Epoch 666/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9435 - loss: 0.1374 - val_accuracy: 0.8799 - val_loss: 0.3053\n",
|
|
"Epoch 667/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9425 - loss: 0.1290 - val_accuracy: 0.8873 - val_loss: 0.2988\n",
|
|
"Epoch 668/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9435 - loss: 0.1244 - val_accuracy: 0.8836 - val_loss: 0.3227\n",
|
|
"Epoch 669/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9317 - loss: 0.1394 - val_accuracy: 0.8818 - val_loss: 0.3293\n",
|
|
"Epoch 670/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9349 - loss: 0.1468 - val_accuracy: 0.8873 - val_loss: 0.3126\n",
|
|
"Epoch 671/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9329 - loss: 0.1397 - val_accuracy: 0.8763 - val_loss: 0.3372\n",
|
|
"Epoch 672/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step - accuracy: 0.9314 - loss: 0.1516 - val_accuracy: 0.8845 - val_loss: 0.2993\n",
|
|
"Epoch 673/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9369 - loss: 0.1423 - val_accuracy: 0.8836 - val_loss: 0.3192\n",
|
|
"Epoch 674/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9319 - loss: 0.1428 - val_accuracy: 0.8827 - val_loss: 0.3149\n",
|
|
"Epoch 675/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9441 - loss: 0.1319 - val_accuracy: 0.8808 - val_loss: 0.3016\n",
|
|
"Epoch 676/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9417 - loss: 0.1277 - val_accuracy: 0.8836 - val_loss: 0.3008\n",
|
|
"Epoch 677/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9400 - loss: 0.1317 - val_accuracy: 0.8854 - val_loss: 0.3097\n",
|
|
"Epoch 678/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9364 - loss: 0.1385 - val_accuracy: 0.8726 - val_loss: 0.3223\n",
|
|
"Epoch 679/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9432 - loss: 0.1257 - val_accuracy: 0.8845 - val_loss: 0.3090\n",
|
|
"Epoch 680/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9406 - loss: 0.1320 - val_accuracy: 0.8854 - val_loss: 0.3079\n",
|
|
"Epoch 681/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9411 - loss: 0.1330 - val_accuracy: 0.8818 - val_loss: 0.3077\n",
|
|
"Epoch 682/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9394 - loss: 0.1345 - val_accuracy: 0.8808 - val_loss: 0.3201\n",
|
|
"Epoch 683/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9422 - loss: 0.1291 - val_accuracy: 0.8836 - val_loss: 0.3221\n",
|
|
"Epoch 684/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9445 - loss: 0.1260 - val_accuracy: 0.8799 - val_loss: 0.3119\n",
|
|
"Epoch 685/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9420 - loss: 0.1342 - val_accuracy: 0.8854 - val_loss: 0.3244\n",
|
|
"Epoch 686/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9456 - loss: 0.1264 - val_accuracy: 0.8854 - val_loss: 0.3067\n",
|
|
"Epoch 687/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9418 - loss: 0.1391 - val_accuracy: 0.8836 - val_loss: 0.3162\n",
|
|
"Epoch 688/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9391 - loss: 0.1333 - val_accuracy: 0.8781 - val_loss: 0.3063\n",
|
|
"Epoch 689/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9398 - loss: 0.1343 - val_accuracy: 0.8818 - val_loss: 0.3113\n",
|
|
"Epoch 690/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9412 - loss: 0.1339 - val_accuracy: 0.8808 - val_loss: 0.3191\n",
|
|
"Epoch 691/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9489 - loss: 0.1275 - val_accuracy: 0.8744 - val_loss: 0.3190\n",
|
|
"Epoch 692/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9435 - loss: 0.1286 - val_accuracy: 0.8854 - val_loss: 0.3204\n",
|
|
"Epoch 693/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9402 - loss: 0.1348 - val_accuracy: 0.8808 - val_loss: 0.3052\n",
|
|
"Epoch 694/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9380 - loss: 0.1381 - val_accuracy: 0.8799 - val_loss: 0.3067\n",
|
|
"Epoch 695/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9460 - loss: 0.1261 - val_accuracy: 0.8763 - val_loss: 0.3100\n",
|
|
"Epoch 696/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9383 - loss: 0.1380 - val_accuracy: 0.8735 - val_loss: 0.3271\n",
|
|
"Epoch 697/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9470 - loss: 0.1329 - val_accuracy: 0.8799 - val_loss: 0.3102\n",
|
|
"Epoch 698/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9405 - loss: 0.1279 - val_accuracy: 0.8818 - val_loss: 0.3283\n",
|
|
"Epoch 699/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9380 - loss: 0.1349 - val_accuracy: 0.8818 - val_loss: 0.3195\n",
|
|
"Epoch 700/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9432 - loss: 0.1323 - val_accuracy: 0.8772 - val_loss: 0.2982\n",
|
|
"Epoch 701/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9437 - loss: 0.1270 - val_accuracy: 0.8763 - val_loss: 0.3265\n",
|
|
"Epoch 702/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9360 - loss: 0.1333 - val_accuracy: 0.8863 - val_loss: 0.3028\n",
|
|
"Epoch 703/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9476 - loss: 0.1193 - val_accuracy: 0.8818 - val_loss: 0.3300\n",
|
|
"Epoch 704/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9391 - loss: 0.1322 - val_accuracy: 0.8781 - val_loss: 0.3052\n",
|
|
"Epoch 705/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9410 - loss: 0.1304 - val_accuracy: 0.8772 - val_loss: 0.3267\n",
|
|
"Epoch 706/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9303 - loss: 0.1451 - val_accuracy: 0.8790 - val_loss: 0.3464\n",
|
|
"Epoch 707/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9331 - loss: 0.1419 - val_accuracy: 0.8808 - val_loss: 0.3013\n",
|
|
"Epoch 708/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9268 - loss: 0.1479 - val_accuracy: 0.8882 - val_loss: 0.3317\n",
|
|
"Epoch 709/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9402 - loss: 0.1342 - val_accuracy: 0.8799 - val_loss: 0.3104\n",
|
|
"Epoch 710/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9476 - loss: 0.1256 - val_accuracy: 0.8873 - val_loss: 0.3118\n",
|
|
"Epoch 711/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9394 - loss: 0.1327 - val_accuracy: 0.8900 - val_loss: 0.3075\n",
|
|
"Epoch 712/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9382 - loss: 0.1354 - val_accuracy: 0.8845 - val_loss: 0.3096\n",
|
|
"Epoch 713/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9351 - loss: 0.1376 - val_accuracy: 0.8799 - val_loss: 0.3393\n",
|
|
"Epoch 714/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9425 - loss: 0.1265 - val_accuracy: 0.8882 - val_loss: 0.3086\n",
|
|
"Epoch 715/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9415 - loss: 0.1365 - val_accuracy: 0.8836 - val_loss: 0.3190\n",
|
|
"Epoch 716/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9387 - loss: 0.1340 - val_accuracy: 0.8808 - val_loss: 0.3389\n",
|
|
"Epoch 717/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9417 - loss: 0.1336 - val_accuracy: 0.8918 - val_loss: 0.3246\n",
|
|
"Epoch 718/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9433 - loss: 0.1355 - val_accuracy: 0.8818 - val_loss: 0.3173\n",
|
|
"Epoch 719/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9367 - loss: 0.1417 - val_accuracy: 0.8873 - val_loss: 0.3200\n",
|
|
"Epoch 720/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9469 - loss: 0.1229 - val_accuracy: 0.8818 - val_loss: 0.3192\n",
|
|
"Epoch 721/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9407 - loss: 0.1385 - val_accuracy: 0.8836 - val_loss: 0.3156\n",
|
|
"Epoch 722/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9421 - loss: 0.1357 - val_accuracy: 0.8827 - val_loss: 0.3394\n",
|
|
"Epoch 723/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9402 - loss: 0.1305 - val_accuracy: 0.8836 - val_loss: 0.3056\n",
|
|
"Epoch 724/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9417 - loss: 0.1235 - val_accuracy: 0.8845 - val_loss: 0.3306\n",
|
|
"Epoch 725/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9432 - loss: 0.1266 - val_accuracy: 0.8845 - val_loss: 0.3117\n",
|
|
"Epoch 726/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9406 - loss: 0.1314 - val_accuracy: 0.8836 - val_loss: 0.3376\n",
|
|
"Epoch 727/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9512 - loss: 0.1272 - val_accuracy: 0.8909 - val_loss: 0.3231\n",
|
|
"Epoch 728/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9451 - loss: 0.1279 - val_accuracy: 0.8735 - val_loss: 0.3387\n",
|
|
"Epoch 729/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9417 - loss: 0.1455 - val_accuracy: 0.8799 - val_loss: 0.3202\n",
|
|
"Epoch 730/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9455 - loss: 0.1326 - val_accuracy: 0.8845 - val_loss: 0.3135\n",
|
|
"Epoch 731/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9389 - loss: 0.1332 - val_accuracy: 0.8827 - val_loss: 0.3286\n",
|
|
"Epoch 732/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9365 - loss: 0.1382 - val_accuracy: 0.8763 - val_loss: 0.3393\n",
|
|
"Epoch 733/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9415 - loss: 0.1233 - val_accuracy: 0.8863 - val_loss: 0.3259\n",
|
|
"Epoch 734/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9419 - loss: 0.1349 - val_accuracy: 0.8845 - val_loss: 0.3510\n",
|
|
"Epoch 735/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9415 - loss: 0.1354 - val_accuracy: 0.8799 - val_loss: 0.3447\n",
|
|
"Epoch 736/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9397 - loss: 0.1418 - val_accuracy: 0.8753 - val_loss: 0.3170\n",
|
|
"Epoch 737/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9391 - loss: 0.1294 - val_accuracy: 0.8799 - val_loss: 0.3207\n",
|
|
"Epoch 738/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9432 - loss: 0.1322 - val_accuracy: 0.8790 - val_loss: 0.3411\n",
|
|
"Epoch 739/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9311 - loss: 0.1462 - val_accuracy: 0.8863 - val_loss: 0.3101\n",
|
|
"Epoch 740/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9390 - loss: 0.1311 - val_accuracy: 0.8753 - val_loss: 0.3227\n",
|
|
"Epoch 741/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9419 - loss: 0.1335 - val_accuracy: 0.8818 - val_loss: 0.3357\n",
|
|
"Epoch 742/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9450 - loss: 0.1292 - val_accuracy: 0.8845 - val_loss: 0.3269\n",
|
|
"Epoch 743/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9372 - loss: 0.1343 - val_accuracy: 0.8836 - val_loss: 0.3220\n",
|
|
"Epoch 744/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9442 - loss: 0.1265 - val_accuracy: 0.8808 - val_loss: 0.3227\n",
|
|
"Epoch 745/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9334 - loss: 0.1394 - val_accuracy: 0.8882 - val_loss: 0.3156\n",
|
|
"Epoch 746/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9421 - loss: 0.1285 - val_accuracy: 0.8882 - val_loss: 0.3114\n",
|
|
"Epoch 747/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9487 - loss: 0.1157 - val_accuracy: 0.8799 - val_loss: 0.3216\n",
|
|
"Epoch 748/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9441 - loss: 0.1298 - val_accuracy: 0.8882 - val_loss: 0.3410\n",
|
|
"Epoch 749/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9353 - loss: 0.1474 - val_accuracy: 0.8763 - val_loss: 0.3477\n",
|
|
"Epoch 750/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9399 - loss: 0.1337 - val_accuracy: 0.8900 - val_loss: 0.3124\n",
|
|
"Epoch 751/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9427 - loss: 0.1324 - val_accuracy: 0.8726 - val_loss: 0.3387\n",
|
|
"Epoch 752/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9418 - loss: 0.1259 - val_accuracy: 0.8799 - val_loss: 0.3163\n",
|
|
"Epoch 753/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9439 - loss: 0.1244 - val_accuracy: 0.8836 - val_loss: 0.3248\n",
|
|
"Epoch 754/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9512 - loss: 0.1167 - val_accuracy: 0.8854 - val_loss: 0.3085\n",
|
|
"Epoch 755/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9387 - loss: 0.1323 - val_accuracy: 0.8726 - val_loss: 0.3808\n",
|
|
"Epoch 756/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9379 - loss: 0.1266 - val_accuracy: 0.8772 - val_loss: 0.3421\n",
|
|
"Epoch 757/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9450 - loss: 0.1236 - val_accuracy: 0.8845 - val_loss: 0.3329\n",
|
|
"Epoch 758/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9457 - loss: 0.1269 - val_accuracy: 0.8854 - val_loss: 0.3141\n",
|
|
"Epoch 759/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9489 - loss: 0.1175 - val_accuracy: 0.8882 - val_loss: 0.3306\n",
|
|
"Epoch 760/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9506 - loss: 0.1174 - val_accuracy: 0.8818 - val_loss: 0.3226\n",
|
|
"Epoch 761/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9469 - loss: 0.1239 - val_accuracy: 0.8579 - val_loss: 0.4195\n",
|
|
"Epoch 762/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9285 - loss: 0.1516 - val_accuracy: 0.8790 - val_loss: 0.3428\n",
|
|
"Epoch 763/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9441 - loss: 0.1295 - val_accuracy: 0.8763 - val_loss: 0.3332\n",
|
|
"Epoch 764/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9419 - loss: 0.1309 - val_accuracy: 0.8891 - val_loss: 0.3375\n",
|
|
"Epoch 765/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9405 - loss: 0.1332 - val_accuracy: 0.8607 - val_loss: 0.4154\n",
|
|
"Epoch 766/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9297 - loss: 0.1504 - val_accuracy: 0.8790 - val_loss: 0.3271\n",
|
|
"Epoch 767/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9472 - loss: 0.1207 - val_accuracy: 0.8873 - val_loss: 0.3392\n",
|
|
"Epoch 768/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9485 - loss: 0.1249 - val_accuracy: 0.8818 - val_loss: 0.3190\n",
|
|
"Epoch 769/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9399 - loss: 0.1357 - val_accuracy: 0.8909 - val_loss: 0.3220\n",
|
|
"Epoch 770/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9507 - loss: 0.1188 - val_accuracy: 0.8799 - val_loss: 0.3462\n",
|
|
"Epoch 771/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9506 - loss: 0.1163 - val_accuracy: 0.8781 - val_loss: 0.3189\n",
|
|
"Epoch 772/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9406 - loss: 0.1335 - val_accuracy: 0.8753 - val_loss: 0.3451\n",
|
|
"Epoch 773/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9468 - loss: 0.1231 - val_accuracy: 0.8753 - val_loss: 0.3340\n",
|
|
"Epoch 774/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9416 - loss: 0.1386 - val_accuracy: 0.8781 - val_loss: 0.3442\n",
|
|
"Epoch 775/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9481 - loss: 0.1227 - val_accuracy: 0.8808 - val_loss: 0.3338\n",
|
|
"Epoch 776/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9377 - loss: 0.1323 - val_accuracy: 0.8781 - val_loss: 0.3339\n",
|
|
"Epoch 777/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9422 - loss: 0.1292 - val_accuracy: 0.8790 - val_loss: 0.3234\n",
|
|
"Epoch 778/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9445 - loss: 0.1206 - val_accuracy: 0.8836 - val_loss: 0.3439\n",
|
|
"Epoch 779/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9521 - loss: 0.1152 - val_accuracy: 0.8753 - val_loss: 0.3489\n",
|
|
"Epoch 780/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9475 - loss: 0.1172 - val_accuracy: 0.8744 - val_loss: 0.3424\n",
|
|
"Epoch 781/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9469 - loss: 0.1283 - val_accuracy: 0.8717 - val_loss: 0.3462\n",
|
|
"Epoch 782/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9511 - loss: 0.1249 - val_accuracy: 0.8882 - val_loss: 0.3344\n",
|
|
"Epoch 783/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9460 - loss: 0.1282 - val_accuracy: 0.8836 - val_loss: 0.3359\n",
|
|
"Epoch 784/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9523 - loss: 0.1194 - val_accuracy: 0.8863 - val_loss: 0.3435\n",
|
|
"Epoch 785/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9453 - loss: 0.1256 - val_accuracy: 0.8818 - val_loss: 0.3393\n",
|
|
"Epoch 786/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9466 - loss: 0.1191 - val_accuracy: 0.8753 - val_loss: 0.3582\n",
|
|
"Epoch 787/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9433 - loss: 0.1279 - val_accuracy: 0.8909 - val_loss: 0.3191\n",
|
|
"Epoch 788/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9519 - loss: 0.1158 - val_accuracy: 0.8744 - val_loss: 0.3344\n",
|
|
"Epoch 789/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9512 - loss: 0.1142 - val_accuracy: 0.8827 - val_loss: 0.3471\n",
|
|
"Epoch 790/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9463 - loss: 0.1272 - val_accuracy: 0.8827 - val_loss: 0.3505\n",
|
|
"Epoch 791/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9340 - loss: 0.1461 - val_accuracy: 0.8753 - val_loss: 0.3447\n",
|
|
"Epoch 792/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9444 - loss: 0.1229 - val_accuracy: 0.8827 - val_loss: 0.3225\n",
|
|
"Epoch 793/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9517 - loss: 0.1147 - val_accuracy: 0.8753 - val_loss: 0.3423\n",
|
|
"Epoch 794/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9437 - loss: 0.1349 - val_accuracy: 0.8854 - val_loss: 0.3520\n",
|
|
"Epoch 795/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9451 - loss: 0.1210 - val_accuracy: 0.8818 - val_loss: 0.3294\n",
|
|
"Epoch 796/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9479 - loss: 0.1221 - val_accuracy: 0.8671 - val_loss: 0.3699\n",
|
|
"Epoch 797/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9463 - loss: 0.1265 - val_accuracy: 0.8863 - val_loss: 0.3447\n",
|
|
"Epoch 798/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9477 - loss: 0.1215 - val_accuracy: 0.8863 - val_loss: 0.3457\n",
|
|
"Epoch 799/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9458 - loss: 0.1298 - val_accuracy: 0.8753 - val_loss: 0.3232\n",
|
|
"Epoch 800/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9448 - loss: 0.1277 - val_accuracy: 0.8827 - val_loss: 0.3468\n",
|
|
"Epoch 801/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9451 - loss: 0.1197 - val_accuracy: 0.8818 - val_loss: 0.3373\n",
|
|
"Epoch 802/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9498 - loss: 0.1165 - val_accuracy: 0.8744 - val_loss: 0.3489\n",
|
|
"Epoch 803/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9553 - loss: 0.1058 - val_accuracy: 0.8863 - val_loss: 0.3723\n",
|
|
"Epoch 804/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9379 - loss: 0.1317 - val_accuracy: 0.8827 - val_loss: 0.3248\n",
|
|
"Epoch 805/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9438 - loss: 0.1277 - val_accuracy: 0.8882 - val_loss: 0.3455\n",
|
|
"Epoch 806/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9430 - loss: 0.1236 - val_accuracy: 0.8882 - val_loss: 0.3254\n",
|
|
"Epoch 807/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9458 - loss: 0.1220 - val_accuracy: 0.8799 - val_loss: 0.3416\n",
|
|
"Epoch 808/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9415 - loss: 0.1292 - val_accuracy: 0.8790 - val_loss: 0.3524\n",
|
|
"Epoch 809/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9460 - loss: 0.1209 - val_accuracy: 0.8772 - val_loss: 0.3410\n",
|
|
"Epoch 810/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9487 - loss: 0.1271 - val_accuracy: 0.8863 - val_loss: 0.3485\n",
|
|
"Epoch 811/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9487 - loss: 0.1118 - val_accuracy: 0.8781 - val_loss: 0.3547\n",
|
|
"Epoch 812/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9460 - loss: 0.1283 - val_accuracy: 0.8781 - val_loss: 0.3516\n",
|
|
"Epoch 813/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9515 - loss: 0.1110 - val_accuracy: 0.8772 - val_loss: 0.3443\n",
|
|
"Epoch 814/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9458 - loss: 0.1192 - val_accuracy: 0.8772 - val_loss: 0.3470\n",
|
|
"Epoch 815/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9313 - loss: 0.1403 - val_accuracy: 0.8873 - val_loss: 0.3427\n",
|
|
"Epoch 816/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9458 - loss: 0.1252 - val_accuracy: 0.8753 - val_loss: 0.3468\n",
|
|
"Epoch 817/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9398 - loss: 0.1321 - val_accuracy: 0.8909 - val_loss: 0.3539\n",
|
|
"Epoch 818/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9513 - loss: 0.1120 - val_accuracy: 0.8772 - val_loss: 0.3525\n",
|
|
"Epoch 819/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9417 - loss: 0.1268 - val_accuracy: 0.8653 - val_loss: 0.3714\n",
|
|
"Epoch 820/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9508 - loss: 0.1175 - val_accuracy: 0.8863 - val_loss: 0.3388\n",
|
|
"Epoch 821/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9474 - loss: 0.1209 - val_accuracy: 0.8808 - val_loss: 0.3466\n",
|
|
"Epoch 822/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9504 - loss: 0.1155 - val_accuracy: 0.8808 - val_loss: 0.3402\n",
|
|
"Epoch 823/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9399 - loss: 0.1267 - val_accuracy: 0.8781 - val_loss: 0.3440\n",
|
|
"Epoch 824/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9428 - loss: 0.1277 - val_accuracy: 0.8863 - val_loss: 0.3367\n",
|
|
"Epoch 825/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9437 - loss: 0.1291 - val_accuracy: 0.8854 - val_loss: 0.3322\n",
|
|
"Epoch 826/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9498 - loss: 0.1158 - val_accuracy: 0.8781 - val_loss: 0.3475\n",
|
|
"Epoch 827/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9525 - loss: 0.1141 - val_accuracy: 0.8808 - val_loss: 0.3315\n",
|
|
"Epoch 828/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9513 - loss: 0.1145 - val_accuracy: 0.8827 - val_loss: 0.3492\n",
|
|
"Epoch 829/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9507 - loss: 0.1164 - val_accuracy: 0.8836 - val_loss: 0.3392\n",
|
|
"Epoch 830/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9521 - loss: 0.1146 - val_accuracy: 0.8616 - val_loss: 0.4139\n",
|
|
"Epoch 831/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9478 - loss: 0.1190 - val_accuracy: 0.8689 - val_loss: 0.3568\n",
|
|
"Epoch 832/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9416 - loss: 0.1297 - val_accuracy: 0.8735 - val_loss: 0.3364\n",
|
|
"Epoch 833/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9488 - loss: 0.1196 - val_accuracy: 0.8854 - val_loss: 0.3420\n",
|
|
"Epoch 834/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9368 - loss: 0.1442 - val_accuracy: 0.8808 - val_loss: 0.3349\n",
|
|
"Epoch 835/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9547 - loss: 0.1139 - val_accuracy: 0.8735 - val_loss: 0.3993\n",
|
|
"Epoch 836/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9463 - loss: 0.1235 - val_accuracy: 0.8671 - val_loss: 0.3501\n",
|
|
"Epoch 837/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9524 - loss: 0.1162 - val_accuracy: 0.8937 - val_loss: 0.3394\n",
|
|
"Epoch 838/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9425 - loss: 0.1257 - val_accuracy: 0.8616 - val_loss: 0.4545\n",
|
|
"Epoch 839/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9410 - loss: 0.1393 - val_accuracy: 0.8808 - val_loss: 0.3491\n",
|
|
"Epoch 840/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9469 - loss: 0.1153 - val_accuracy: 0.8763 - val_loss: 0.3554\n",
|
|
"Epoch 841/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9565 - loss: 0.1056 - val_accuracy: 0.8799 - val_loss: 0.3614\n",
|
|
"Epoch 842/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9457 - loss: 0.1218 - val_accuracy: 0.8781 - val_loss: 0.3602\n",
|
|
"Epoch 843/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9479 - loss: 0.1134 - val_accuracy: 0.8717 - val_loss: 0.3680\n",
|
|
"Epoch 844/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9415 - loss: 0.1257 - val_accuracy: 0.8808 - val_loss: 0.3475\n",
|
|
"Epoch 845/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9480 - loss: 0.1192 - val_accuracy: 0.8744 - val_loss: 0.3457\n",
|
|
"Epoch 846/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9508 - loss: 0.1121 - val_accuracy: 0.8781 - val_loss: 0.3673\n",
|
|
"Epoch 847/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9521 - loss: 0.1115 - val_accuracy: 0.8625 - val_loss: 0.3666\n",
|
|
"Epoch 848/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9406 - loss: 0.1408 - val_accuracy: 0.8790 - val_loss: 0.3443\n",
|
|
"Epoch 849/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9402 - loss: 0.1285 - val_accuracy: 0.8854 - val_loss: 0.3504\n",
|
|
"Epoch 850/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9548 - loss: 0.1094 - val_accuracy: 0.8616 - val_loss: 0.3906\n",
|
|
"Epoch 851/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9408 - loss: 0.1330 - val_accuracy: 0.8827 - val_loss: 0.3809\n",
|
|
"Epoch 852/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9394 - loss: 0.1339 - val_accuracy: 0.8845 - val_loss: 0.3599\n",
|
|
"Epoch 853/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9440 - loss: 0.1138 - val_accuracy: 0.8772 - val_loss: 0.3529\n",
|
|
"Epoch 854/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9426 - loss: 0.1225 - val_accuracy: 0.8790 - val_loss: 0.3734\n",
|
|
"Epoch 855/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9514 - loss: 0.1288 - val_accuracy: 0.8873 - val_loss: 0.3431\n",
|
|
"Epoch 856/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9466 - loss: 0.1262 - val_accuracy: 0.8781 - val_loss: 0.3609\n",
|
|
"Epoch 857/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9471 - loss: 0.1132 - val_accuracy: 0.8698 - val_loss: 0.3577\n",
|
|
"Epoch 858/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9455 - loss: 0.1229 - val_accuracy: 0.8753 - val_loss: 0.3541\n",
|
|
"Epoch 859/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9506 - loss: 0.1186 - val_accuracy: 0.8735 - val_loss: 0.3856\n",
|
|
"Epoch 860/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9622 - loss: 0.1005 - val_accuracy: 0.8845 - val_loss: 0.3655\n",
|
|
"Epoch 861/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9506 - loss: 0.1141 - val_accuracy: 0.8818 - val_loss: 0.3565\n",
|
|
"Epoch 862/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9538 - loss: 0.1052 - val_accuracy: 0.8735 - val_loss: 0.3479\n",
|
|
"Epoch 863/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9562 - loss: 0.1068 - val_accuracy: 0.8763 - val_loss: 0.3640\n",
|
|
"Epoch 864/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9598 - loss: 0.1000 - val_accuracy: 0.8753 - val_loss: 0.3714\n",
|
|
"Epoch 865/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9437 - loss: 0.1289 - val_accuracy: 0.8726 - val_loss: 0.3554\n",
|
|
"Epoch 866/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9505 - loss: 0.1085 - val_accuracy: 0.8808 - val_loss: 0.3437\n",
|
|
"Epoch 867/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9533 - loss: 0.1079 - val_accuracy: 0.8946 - val_loss: 0.3623\n",
|
|
"Epoch 868/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9514 - loss: 0.1126 - val_accuracy: 0.8579 - val_loss: 0.3930\n",
|
|
"Epoch 869/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9350 - loss: 0.1482 - val_accuracy: 0.8854 - val_loss: 0.3508\n",
|
|
"Epoch 870/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9309 - loss: 0.1685 - val_accuracy: 0.8863 - val_loss: 0.3581\n",
|
|
"Epoch 871/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9523 - loss: 0.1139 - val_accuracy: 0.8744 - val_loss: 0.3709\n",
|
|
"Epoch 872/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9496 - loss: 0.1149 - val_accuracy: 0.8799 - val_loss: 0.3720\n",
|
|
"Epoch 873/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9475 - loss: 0.1241 - val_accuracy: 0.8698 - val_loss: 0.3860\n",
|
|
"Epoch 874/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9434 - loss: 0.1232 - val_accuracy: 0.8744 - val_loss: 0.3644\n",
|
|
"Epoch 875/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9493 - loss: 0.1170 - val_accuracy: 0.8717 - val_loss: 0.3571\n",
|
|
"Epoch 876/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9490 - loss: 0.1183 - val_accuracy: 0.8818 - val_loss: 0.3530\n",
|
|
"Epoch 877/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9526 - loss: 0.1092 - val_accuracy: 0.8799 - val_loss: 0.3569\n",
|
|
"Epoch 878/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9579 - loss: 0.1063 - val_accuracy: 0.8873 - val_loss: 0.3543\n",
|
|
"Epoch 879/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9530 - loss: 0.1157 - val_accuracy: 0.8698 - val_loss: 0.3622\n",
|
|
"Epoch 880/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9498 - loss: 0.1121 - val_accuracy: 0.8891 - val_loss: 0.3410\n",
|
|
"Epoch 881/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9476 - loss: 0.1226 - val_accuracy: 0.8671 - val_loss: 0.3937\n",
|
|
"Epoch 882/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9477 - loss: 0.1253 - val_accuracy: 0.8827 - val_loss: 0.3450\n",
|
|
"Epoch 883/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9575 - loss: 0.1036 - val_accuracy: 0.8790 - val_loss: 0.3556\n",
|
|
"Epoch 884/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9537 - loss: 0.1117 - val_accuracy: 0.8689 - val_loss: 0.3839\n",
|
|
"Epoch 885/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9528 - loss: 0.1097 - val_accuracy: 0.8854 - val_loss: 0.3629\n",
|
|
"Epoch 886/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9444 - loss: 0.1212 - val_accuracy: 0.8698 - val_loss: 0.3646\n",
|
|
"Epoch 887/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9521 - loss: 0.1126 - val_accuracy: 0.8818 - val_loss: 0.3873\n",
|
|
"Epoch 888/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9431 - loss: 0.1222 - val_accuracy: 0.8863 - val_loss: 0.3591\n",
|
|
"Epoch 889/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9603 - loss: 0.0978 - val_accuracy: 0.8808 - val_loss: 0.3576\n",
|
|
"Epoch 890/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9542 - loss: 0.1059 - val_accuracy: 0.8882 - val_loss: 0.3638\n",
|
|
"Epoch 891/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9489 - loss: 0.1217 - val_accuracy: 0.8744 - val_loss: 0.4065\n",
|
|
"Epoch 892/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9389 - loss: 0.1318 - val_accuracy: 0.8790 - val_loss: 0.3766\n",
|
|
"Epoch 893/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9502 - loss: 0.1159 - val_accuracy: 0.8744 - val_loss: 0.3491\n",
|
|
"Epoch 894/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9542 - loss: 0.1091 - val_accuracy: 0.8744 - val_loss: 0.3442\n",
|
|
"Epoch 895/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9407 - loss: 0.1319 - val_accuracy: 0.8763 - val_loss: 0.3637\n",
|
|
"Epoch 896/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9419 - loss: 0.1256 - val_accuracy: 0.8836 - val_loss: 0.3568\n",
|
|
"Epoch 897/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9526 - loss: 0.1112 - val_accuracy: 0.8698 - val_loss: 0.3622\n",
|
|
"Epoch 898/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9502 - loss: 0.1140 - val_accuracy: 0.8827 - val_loss: 0.3431\n",
|
|
"Epoch 899/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9521 - loss: 0.1087 - val_accuracy: 0.8753 - val_loss: 0.3746\n",
|
|
"Epoch 900/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9518 - loss: 0.1068 - val_accuracy: 0.8698 - val_loss: 0.3618\n",
|
|
"Epoch 901/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9536 - loss: 0.1149 - val_accuracy: 0.8698 - val_loss: 0.3579\n",
|
|
"Epoch 902/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9446 - loss: 0.1258 - val_accuracy: 0.8708 - val_loss: 0.3862\n",
|
|
"Epoch 903/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9443 - loss: 0.1235 - val_accuracy: 0.8726 - val_loss: 0.3596\n",
|
|
"Epoch 904/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9536 - loss: 0.1078 - val_accuracy: 0.8781 - val_loss: 0.3543\n",
|
|
"Epoch 905/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9485 - loss: 0.1180 - val_accuracy: 0.8726 - val_loss: 0.3703\n",
|
|
"Epoch 906/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9534 - loss: 0.1170 - val_accuracy: 0.8753 - val_loss: 0.3871\n",
|
|
"Epoch 907/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9522 - loss: 0.1147 - val_accuracy: 0.8772 - val_loss: 0.3704\n",
|
|
"Epoch 908/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9535 - loss: 0.1177 - val_accuracy: 0.8863 - val_loss: 0.3643\n",
|
|
"Epoch 909/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9519 - loss: 0.1124 - val_accuracy: 0.8726 - val_loss: 0.3753\n",
|
|
"Epoch 910/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9499 - loss: 0.1129 - val_accuracy: 0.8854 - val_loss: 0.3650\n",
|
|
"Epoch 911/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9522 - loss: 0.1098 - val_accuracy: 0.8680 - val_loss: 0.4154\n",
|
|
"Epoch 912/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9458 - loss: 0.1136 - val_accuracy: 0.8808 - val_loss: 0.3600\n",
|
|
"Epoch 913/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9492 - loss: 0.1207 - val_accuracy: 0.8827 - val_loss: 0.3607\n",
|
|
"Epoch 914/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9555 - loss: 0.1009 - val_accuracy: 0.8836 - val_loss: 0.3696\n",
|
|
"Epoch 915/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9521 - loss: 0.1169 - val_accuracy: 0.8772 - val_loss: 0.3675\n",
|
|
"Epoch 916/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9481 - loss: 0.1107 - val_accuracy: 0.8799 - val_loss: 0.3648\n",
|
|
"Epoch 917/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9514 - loss: 0.1176 - val_accuracy: 0.8579 - val_loss: 0.4192\n",
|
|
"Epoch 918/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9450 - loss: 0.1278 - val_accuracy: 0.8689 - val_loss: 0.3715\n",
|
|
"Epoch 919/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9552 - loss: 0.1062 - val_accuracy: 0.8781 - val_loss: 0.3626\n",
|
|
"Epoch 920/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9541 - loss: 0.1045 - val_accuracy: 0.8698 - val_loss: 0.3619\n",
|
|
"Epoch 921/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9493 - loss: 0.1190 - val_accuracy: 0.8753 - val_loss: 0.3713\n",
|
|
"Epoch 922/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9447 - loss: 0.1210 - val_accuracy: 0.8763 - val_loss: 0.3873\n",
|
|
"Epoch 923/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9479 - loss: 0.1185 - val_accuracy: 0.8836 - val_loss: 0.3723\n",
|
|
"Epoch 924/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9464 - loss: 0.1175 - val_accuracy: 0.8744 - val_loss: 0.3806\n",
|
|
"Epoch 925/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9578 - loss: 0.1018 - val_accuracy: 0.8799 - val_loss: 0.3779\n",
|
|
"Epoch 926/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9531 - loss: 0.1117 - val_accuracy: 0.8616 - val_loss: 0.4099\n",
|
|
"Epoch 927/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9400 - loss: 0.1369 - val_accuracy: 0.8845 - val_loss: 0.3643\n",
|
|
"Epoch 928/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9532 - loss: 0.1028 - val_accuracy: 0.8717 - val_loss: 0.3882\n",
|
|
"Epoch 929/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9469 - loss: 0.1175 - val_accuracy: 0.8863 - val_loss: 0.3822\n",
|
|
"Epoch 930/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9505 - loss: 0.1064 - val_accuracy: 0.8744 - val_loss: 0.3988\n",
|
|
"Epoch 931/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9474 - loss: 0.1174 - val_accuracy: 0.8790 - val_loss: 0.3603\n",
|
|
"Epoch 932/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9526 - loss: 0.1128 - val_accuracy: 0.8698 - val_loss: 0.3879\n",
|
|
"Epoch 933/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9530 - loss: 0.1043 - val_accuracy: 0.8698 - val_loss: 0.3573\n",
|
|
"Epoch 934/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9545 - loss: 0.1059 - val_accuracy: 0.8845 - val_loss: 0.3823\n",
|
|
"Epoch 935/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9442 - loss: 0.1268 - val_accuracy: 0.8790 - val_loss: 0.3738\n",
|
|
"Epoch 936/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9566 - loss: 0.1050 - val_accuracy: 0.8818 - val_loss: 0.3742\n",
|
|
"Epoch 937/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9533 - loss: 0.1085 - val_accuracy: 0.8689 - val_loss: 0.3850\n",
|
|
"Epoch 938/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9553 - loss: 0.1007 - val_accuracy: 0.8799 - val_loss: 0.3710\n",
|
|
"Epoch 939/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9514 - loss: 0.1158 - val_accuracy: 0.8808 - val_loss: 0.3881\n",
|
|
"Epoch 940/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9533 - loss: 0.1061 - val_accuracy: 0.8634 - val_loss: 0.4248\n",
|
|
"Epoch 941/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9509 - loss: 0.1129 - val_accuracy: 0.8744 - val_loss: 0.3946\n",
|
|
"Epoch 942/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9552 - loss: 0.1084 - val_accuracy: 0.8726 - val_loss: 0.3590\n",
|
|
"Epoch 943/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9551 - loss: 0.1067 - val_accuracy: 0.8836 - val_loss: 0.3730\n",
|
|
"Epoch 944/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9439 - loss: 0.1287 - val_accuracy: 0.8735 - val_loss: 0.3690\n",
|
|
"Epoch 945/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9509 - loss: 0.1149 - val_accuracy: 0.8781 - val_loss: 0.3866\n",
|
|
"Epoch 946/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9509 - loss: 0.1155 - val_accuracy: 0.8799 - val_loss: 0.3892\n",
|
|
"Epoch 947/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9618 - loss: 0.1046 - val_accuracy: 0.8808 - val_loss: 0.3704\n",
|
|
"Epoch 948/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9491 - loss: 0.1115 - val_accuracy: 0.8763 - val_loss: 0.3681\n",
|
|
"Epoch 949/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9437 - loss: 0.1230 - val_accuracy: 0.8836 - val_loss: 0.3625\n",
|
|
"Epoch 950/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9512 - loss: 0.1109 - val_accuracy: 0.8717 - val_loss: 0.3631\n",
|
|
"Epoch 951/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9602 - loss: 0.1048 - val_accuracy: 0.8717 - val_loss: 0.3707\n",
|
|
"Epoch 952/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9537 - loss: 0.1082 - val_accuracy: 0.8845 - val_loss: 0.3697\n",
|
|
"Epoch 953/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9533 - loss: 0.1110 - val_accuracy: 0.8735 - val_loss: 0.4001\n",
|
|
"Epoch 954/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9448 - loss: 0.1216 - val_accuracy: 0.8753 - val_loss: 0.3954\n",
|
|
"Epoch 955/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9520 - loss: 0.1090 - val_accuracy: 0.8799 - val_loss: 0.3935\n",
|
|
"Epoch 956/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9476 - loss: 0.1127 - val_accuracy: 0.8744 - val_loss: 0.3929\n",
|
|
"Epoch 957/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9526 - loss: 0.1028 - val_accuracy: 0.8799 - val_loss: 0.3741\n",
|
|
"Epoch 958/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9479 - loss: 0.1066 - val_accuracy: 0.8836 - val_loss: 0.3754\n",
|
|
"Epoch 959/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9512 - loss: 0.1052 - val_accuracy: 0.8689 - val_loss: 0.3619\n",
|
|
"Epoch 960/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9590 - loss: 0.1040 - val_accuracy: 0.8772 - val_loss: 0.3578\n",
|
|
"Epoch 961/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9535 - loss: 0.1082 - val_accuracy: 0.8882 - val_loss: 0.3726\n",
|
|
"Epoch 962/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9481 - loss: 0.1130 - val_accuracy: 0.8753 - val_loss: 0.3845\n",
|
|
"Epoch 963/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9556 - loss: 0.1067 - val_accuracy: 0.8772 - val_loss: 0.3907\n",
|
|
"Epoch 964/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9544 - loss: 0.1105 - val_accuracy: 0.8680 - val_loss: 0.3859\n",
|
|
"Epoch 965/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9518 - loss: 0.1129 - val_accuracy: 0.8726 - val_loss: 0.4016\n",
|
|
"Epoch 966/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9517 - loss: 0.1123 - val_accuracy: 0.8753 - val_loss: 0.4160\n",
|
|
"Epoch 967/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9519 - loss: 0.1057 - val_accuracy: 0.8735 - val_loss: 0.3864\n",
|
|
"Epoch 968/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9538 - loss: 0.1060 - val_accuracy: 0.8753 - val_loss: 0.3817\n",
|
|
"Epoch 969/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9553 - loss: 0.1117 - val_accuracy: 0.8753 - val_loss: 0.3748\n",
|
|
"Epoch 970/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9572 - loss: 0.1043 - val_accuracy: 0.8799 - val_loss: 0.3654\n",
|
|
"Epoch 971/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9516 - loss: 0.1096 - val_accuracy: 0.8772 - val_loss: 0.3756\n",
|
|
"Epoch 972/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9550 - loss: 0.1066 - val_accuracy: 0.8616 - val_loss: 0.4797\n",
|
|
"Epoch 973/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9479 - loss: 0.1214 - val_accuracy: 0.8735 - val_loss: 0.3808\n",
|
|
"Epoch 974/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9584 - loss: 0.1004 - val_accuracy: 0.8680 - val_loss: 0.3958\n",
|
|
"Epoch 975/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9504 - loss: 0.1210 - val_accuracy: 0.8680 - val_loss: 0.4856\n",
|
|
"Epoch 976/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9412 - loss: 0.1393 - val_accuracy: 0.8772 - val_loss: 0.4309\n",
|
|
"Epoch 977/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9545 - loss: 0.1070 - val_accuracy: 0.8781 - val_loss: 0.4104\n",
|
|
"Epoch 978/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9447 - loss: 0.1352 - val_accuracy: 0.8781 - val_loss: 0.3633\n",
|
|
"Epoch 979/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9485 - loss: 0.1155 - val_accuracy: 0.8726 - val_loss: 0.4027\n",
|
|
"Epoch 980/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9441 - loss: 0.1234 - val_accuracy: 0.8735 - val_loss: 0.3668\n",
|
|
"Epoch 981/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9550 - loss: 0.1070 - val_accuracy: 0.8790 - val_loss: 0.3914\n",
|
|
"Epoch 982/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9563 - loss: 0.1001 - val_accuracy: 0.8763 - val_loss: 0.3797\n",
|
|
"Epoch 983/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9519 - loss: 0.1102 - val_accuracy: 0.8799 - val_loss: 0.3767\n",
|
|
"Epoch 984/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9617 - loss: 0.0968 - val_accuracy: 0.8744 - val_loss: 0.3871\n",
|
|
"Epoch 985/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9492 - loss: 0.1192 - val_accuracy: 0.8808 - val_loss: 0.3760\n",
|
|
"Epoch 986/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9507 - loss: 0.1138 - val_accuracy: 0.8836 - val_loss: 0.3957\n",
|
|
"Epoch 987/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9557 - loss: 0.1014 - val_accuracy: 0.8708 - val_loss: 0.3938\n",
|
|
"Epoch 988/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9592 - loss: 0.0977 - val_accuracy: 0.8790 - val_loss: 0.3815\n",
|
|
"Epoch 989/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9491 - loss: 0.1213 - val_accuracy: 0.8854 - val_loss: 0.3666\n",
|
|
"Epoch 990/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9565 - loss: 0.1018 - val_accuracy: 0.8763 - val_loss: 0.3965\n",
|
|
"Epoch 991/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9619 - loss: 0.0954 - val_accuracy: 0.8808 - val_loss: 0.3932\n",
|
|
"Epoch 992/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step - accuracy: 0.9502 - loss: 0.1148 - val_accuracy: 0.8708 - val_loss: 0.3778\n",
|
|
"Epoch 993/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9605 - loss: 0.0996 - val_accuracy: 0.8763 - val_loss: 0.4069\n",
|
|
"Epoch 994/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9473 - loss: 0.1161 - val_accuracy: 0.8763 - val_loss: 0.3945\n",
|
|
"Epoch 995/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9588 - loss: 0.0959 - val_accuracy: 0.8744 - val_loss: 0.4135\n",
|
|
"Epoch 996/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9625 - loss: 0.0901 - val_accuracy: 0.8662 - val_loss: 0.4634\n",
|
|
"Epoch 997/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9454 - loss: 0.1246 - val_accuracy: 0.8708 - val_loss: 0.4124\n",
|
|
"Epoch 998/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9574 - loss: 0.1060 - val_accuracy: 0.8836 - val_loss: 0.3864\n",
|
|
"Epoch 999/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9543 - loss: 0.1107 - val_accuracy: 0.8845 - val_loss: 0.3957\n",
|
|
"Epoch 1000/1000\n",
|
|
"\u001b[1m137/137\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9496 - loss: 0.1262 - val_accuracy: 0.8708 - val_loss: 0.3969\n",
|
|
"\u001b[1m171/171\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step \n",
|
|
"\u001b[1m171/171\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 831us/step\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"documents = build_corpus(['dev-0/in.tsv', 'test-A/in.tsv'])\n",
|
|
"word2vec_model = Word2Vec(sentences=documents, vector_size=100, window=5, min_count=1, workers=4)\n",
|
|
"word2vec_model.save(\"word2vec.model\")\n",
|
|
"\n",
|
|
"dev_texts = read_text_file('dev-0/in.tsv')\n",
|
|
"test_texts = read_text_file('test-A/in.tsv')\n",
|
|
"\n",
|
|
"dev_features = np.array([text_to_vector(text, word2vec_model) for text in dev_texts])\n",
|
|
"test_features = np.array([text_to_vector(text, word2vec_model) for text in test_texts])\n",
|
|
"\n",
|
|
"dev_labels = pd.read_csv('dev-0/expected.tsv', sep='\\t', header=None).values.flatten()\n",
|
|
"X_train, X_valid, y_train, y_valid = train_test_split(dev_features, dev_labels, test_size=0.2, random_state=42)\n",
|
|
"\n",
|
|
"neural_network = Sequential([\n",
|
|
" Dense(64, activation='relu', input_shape=(100,)),\n",
|
|
" Dense(32, activation='relu'),\n",
|
|
" Dense(1, activation='sigmoid')\n",
|
|
"])\n",
|
|
"\n",
|
|
"neural_network.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])\n",
|
|
"\n",
|
|
"training_history = neural_network.fit(X_train, y_train, epochs=1000, batch_size=32, validation_data=(X_valid, y_valid))\n",
|
|
"\n",
|
|
"dev_predictions_raw = neural_network.predict(dev_features)\n",
|
|
"test_predictions_raw = neural_network.predict(test_features)\n",
|
|
"\n",
|
|
"dev_predictions = (dev_predictions_raw > 0.5).astype(int)\n",
|
|
"test_predictions = (test_predictions_raw > 0.5).astype(int)\n",
|
|
"\n",
|
|
"write_predictions_to_file(dev_predictions, 'dev-0/out.tsv')\n",
|
|
"write_predictions_to_file(test_predictions, 'test-A/out.tsv')\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"=== Evaluation Results ===\n",
|
|
"Accuracy: 0.9364\n",
|
|
"\n",
|
|
"Classification Report:\n",
|
|
"\n",
|
|
" precision recall f1-score support\n",
|
|
"\n",
|
|
" 0 0.93 0.89 0.91 1983\n",
|
|
" 1 0.94 0.96 0.95 3469\n",
|
|
"\n",
|
|
" accuracy 0.94 5452\n",
|
|
" macro avg 0.93 0.93 0.93 5452\n",
|
|
"weighted avg 0.94 0.94 0.94 5452\n",
|
|
"\n",
|
|
"==========================\n",
|
|
"\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"dev_pred_labels = pd.read_csv('dev-0/out.tsv', header=None).values.flatten()\n",
|
|
"expected_labels = dev_labels\n",
|
|
"\n",
|
|
"accuracy = accuracy_score(expected_labels, dev_pred_labels)\n",
|
|
"report = classification_report(expected_labels, dev_pred_labels)\n",
|
|
"\n",
|
|
"print(\"=== Evaluation Results ===\")\n",
|
|
"print(f\"Accuracy: {accuracy:.4f}\")\n",
|
|
"print(\"\\nClassification Report:\\n\")\n",
|
|
"print(report)\n",
|
|
"print(\"==========================\\n\")"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "base",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.9.19"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|