model doesn't learn

[hmtkvs]

loss stops decreasing after 6th epoch. I have run the original model proposed.

Epoch 1/50
37831/37831 [==============================] - 646s 17ms/step - loss: 1.2934 - acc: 0.4069 - val_loss: 1.1452 - val_acc: 0.4933
WARNING:tensorflow:From C:\Users\hmtkv\miniconda3\envs\voice\lib\site-packages\keras\callbacks\tensorboard_v1.py:343: The name tf.Summary is deprecated. Please use tf.compat.v1.Summary instead.

Epoch 2/50
37831/37831 [==============================] - 562s 15ms/step - loss: 1.0629 - acc: 0.5535 - val_loss: 1.0023 - val_acc: 0.5854
Epoch 3/50
37831/37831 [==============================] - 575s 15ms/step - loss: 0.9804 - acc: 0.5960 - val_loss: 0.9605 - val_acc: 0.6059
Epoch 4/50
37831/37831 [==============================] - 645s 17ms/step - loss: 0.9549 - acc: 0.6062 - val_loss: 0.9530 - val_acc: 0.6019
Epoch 5/50
37831/37831 [==============================] - 626s 17ms/step - loss: 0.9366 - acc: 0.6144 - val_loss: 0.9421 - val_acc: 0.6145
Epoch 6/50
37831/37831 [==============================] - 629s 17ms/step - loss: 0.9300 - acc: 0.6156 - val_loss: 0.9327 - val_acc: 0.6120
Epoch 7/50
37831/37831 [==============================] - 544s 14ms/step - loss: 0.9212 - acc: 0.6218 - val_loss: 0.9239 - val_acc: 0.6161
Epoch 8/50
37831/37831 [==============================] - 610s 16ms/step - loss: 0.9136 - acc: 0.6247 - val_loss: 0.9398 - val_acc: 0.6001
Epoch 9/50
37831/37831 [==============================] - 584s 15ms/step - loss: 0.9081 - acc: 0.6259 - val_loss: 0.9309 - val_acc: 0.6196
Epoch 10/50
37831/37831 [==============================] - 596s 16ms/step - loss: 0.9053 - acc: 0.6294 - val_loss: 0.9182 - val_acc: 0.6219
Epoch 11/50
37831/37831 [==============================] - 569s 15ms/step - loss: 0.9021 - acc: 0.6310 - val_loss: 0.9335 - val_acc: 0.6093
Epoch 12/50
37831/37831 [==============================] - 636s 17ms/step - loss: 0.8967 - acc: 0.6321 - val_loss: 0.9365 - val_acc: 0.6095
Epoch 13/50
37831/37831 [==============================] - 596s 16ms/step - loss: 0.8950 - acc: 0.6323 - val_loss: 0.9366 - val_acc: 0.6045
Epoch 14/50
37831/37831 [==============================] - 567s 15ms/step - loss: 0.8917 - acc: 0.6336 - val_loss: 0.9196 - val_acc: 0.6196
Epoch 15/50
37831/37831 [==============================] - 511s 13ms/step - loss: 0.8883 - acc: 0.6364 - val_loss: 0.9240 - val_acc: 0.6159
Epoch 16/50
37831/37831 [==============================] - 517s 14ms/step - loss: 0.8846 - acc: 0.6380 - val_loss: 0.9149 - val_acc: 0.6217
Epoch 17/50
37831/37831 [==============================] - 569s 15ms/step - loss: 0.8834 - acc: 0.6382 - val_loss: 0.9154 - val_acc: 0.6224
Epoch 18/50
37831/37831 [==============================] - 552s 15ms/step - loss: 0.8813 - acc: 0.6394 - val_loss: 0.9192 - val_acc: 0.6173
Epoch 19/50
37831/37831 [==============================] - 547s 14ms/step - loss: 0.8770 - acc: 0.6395 - val_loss: 0.9123 - val_acc: 0.6243
Epoch 20/50
37831/37831 [==============================] - 541s 14ms/step - loss: 0.8782 - acc: 0.6387 - val_loss: 0.9128 - val_acc: 0.6243
Epoch 21/50
37831/37831 [==============================] - 499s 13ms/step - loss: 0.8747 - acc: 0.6405 - val_loss: 0.9135 - val_acc: 0.6214
Epoch 22/50
37831/37831 [==============================] - 495s 13ms/step - loss: 0.8718 - acc: 0.6422 - val_loss: 0.9158 - val_acc: 0.6254
Epoch 23/50
37831/37831 [==============================] - 502s 13ms/step - loss: 0.8687 - acc: 0.6428 - val_loss: 0.9141 - val_acc: 0.6229
Epoch 24/50
37831/37831 [==============================] - 502s 13ms/step - loss: 0.8685 - acc: 0.6441 - val_loss: 0.9259 - val_acc: 0.6181
Epoch 25/50
37831/37831 [==============================] - 496s 13ms/step - loss: 0.8670 - acc: 0.6445 - val_loss: 0.9172 - val_acc: 0.6224
Epoch 26/50
37831/37831 [==============================] - 500s 13ms/step - loss: 0.8630 - acc: 0.6449 - val_loss: 0.9139 - val_acc: 0.6253
Epoch 27/50
37831/37831 [==============================] - 498s 13ms/step - loss: 0.8664 - acc: 0.6452 - val_loss: 0.9140 - val_acc: 0.6256
Epoch 28/50
37831/37831 [==============================] - 499s 13ms/step - loss: 0.8607 - acc: 0.6485 - val_loss: 0.9216 - val_acc: 0.6204
Epoch 29/50
37831/37831 [==============================] - 497s 13ms/step - loss: 0.8587 - acc: 0.6470 - val_loss: 0.9201 - val_acc: 0.6235
Epoch 30/50
37831/37831 [==============================] - 519s 14ms/step - loss: 0.8573 - acc: 0.6503 - val_loss: 0.9126 - val_acc: 0.6276
Epoch 31/50
37831/37831 [==============================] - 539s 14ms/step - loss: 0.8547 - acc: 0.6507 - val_loss: 0.9187 - val_acc: 0.6156
Epoch 32/50
37831/37831 [==============================] - 534s 14ms/step - loss: 0.8540 - acc: 0.6514 - val_loss: 0.9169 - val_acc: 0.6205
Epoch 33/50
37831/37831 [==============================] - 531s 14ms/step - loss: 0.8525 - acc: 0.6509 - val_loss: 0.9129 - val_acc: 0.6229
Epoch 34/50
37831/37831 [==============================] - 522s 14ms/step - loss: 0.8490 - acc: 0.6532 - val_loss: 0.9189 - val_acc: 0.6230
Epoch 35/50
37831/37831 [==============================] - 510s 13ms/step - loss: 0.8508 - acc: 0.6509 - val_loss: 0.9140 - val_acc: 0.6247
Epoch 36/50
37831/37831 [==============================] - 520s 14ms/step - loss: 0.8471 - acc: 0.6526 - val_loss: 0.9153 - val_acc: 0.6223
Epoch 37/50
37831/37831 [==============================] - 551s 15ms/step - loss: 0.8435 - acc: 0.6544 - val_loss: 0.9203 - val_acc: 0.6221
Epoch 38/50
37831/37831 [==============================] - 556s 15ms/step - loss: 0.8431 - acc: 0.6535 - val_loss: 0.9227 - val_acc: 0.6165
Epoch 39/50
37831/37831 [==============================] - 539s 14ms/step - loss: 0.8416 - acc: 0.6549 - val_loss: 0.9120 - val_acc: 0.6279
Epoch 40/50
37831/37831 [==============================] - 526s 14ms/step - loss: 0.8421 - acc: 0.6576 - val_loss: 0.9158 - val_acc: 0.6229
Epoch 41/50
37831/37831 [==============================] - 519s 14ms/step - loss: 0.8367 - acc: 0.6571 - val_loss: 0.9210 - val_acc: 0.6176
Epoch 42/50
37831/37831 [==============================] - 534s 14ms/step - loss: 0.8358 - acc: 0.6585 - val_loss: 0.9153 - val_acc: 0.6269
Epoch 43/50
37831/37831 [==============================] - 520s 14ms/step - loss: 0.8371 - acc: 0.6589 - val_loss: 0.9183 - val_acc: 0.6229
Epoch 44/50
37831/37831 [==============================] - 522s 14ms/step - loss: 0.8355 - acc: 0.6588 - val_loss: 0.9215 - val_acc: 0.6228
Epoch 45/50
37831/37831 [==============================] - 502s 13ms/step - loss: 0.8325 - acc: 0.6585 - val_loss: 0.9206 - val_acc: 0.6231
Epoch 46/50
37831/37831 [==============================] - 498s 13ms/step - loss: 0.8321 - acc: 0.6606 - val_loss: 0.9210 - val_acc: 0.6186
Epoch 47/50
37831/37831 [==============================] - 499s 13ms/step - loss: 0.8282 - acc: 0.6611 - val_loss: 0.9249 - val_acc: 0.6227
Epoch 48/50
37831/37831 [==============================] - 507s 13ms/step - loss: 0.8279 - acc: 0.6616 - val_loss: 0.9199 - val_acc: 0.6219
Epoch 49/50
37831/37831 [==============================] - 499s 13ms/step - loss: 0.8262 - acc: 0.6620 - val_loss: 0.9245 - val_acc: 0.6217
Epoch 50/50
37831/37831 [==============================] - 498s 13ms/step - loss: 0.8252 - acc: 0.6624 - val_loss: 0.9290 - val_acc: 0.6195

It seems like using such complex network didn't work very well for twitter.