<commit_before>ubuntu@ip-172-31-40-7:~/Text_Generation/code$ cat log_gru.txt
Dataset: ../datasets/poems.txt
corpus length: 923118
total chars: 69
nb sequences: 307693
Vectorization...
Build model...
Iteration Number 1
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 126s - loss: 2.0206 - acc: 0.4054 - val_loss: 1.9534 - val_acc: 0.4136
{'loss': [2.0205905763375553], 'val_loss': [1.9533537864437105], 'val_acc': [0.41355888136511521], 'acc': [0.4054453715967638]}
Best model so far. Saving...
Iteration Number 2
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 127s - loss: 1.8496 - acc: 0.4467 - val_loss: 1.8733 - val_acc: 0.4391
{'loss': [1.8495901757384132], 'val_loss': [1.8733049845830707], 'val_acc': [0.4391199077226004], 'acc': [0.44665128334319004]}
Best model so far. Saving...
Iteration Number 3
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 127s - loss: 1.8109 - acc: 0.4574 - val_loss: 1.8950 - val_acc: 0.4417
{'loss': [1.8108753433806901], 'val_loss': [1.8950475768107411], 'val_acc': [0.44170363509706723], 'acc': [0.45741283911794411]}
Iteration Number 4
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 127s - loss: 1.7965 - acc: 0.4598 - val_loss: 1.8726 - val_acc: 0.4360
{'loss': [1.7964830875350237], 'val_loss': [1.8725598065276123], 'val_acc': [0.4360161848608039], 'acc': [0.45978127513670303]}
Best model so far. Saving...
Iteration Number 5
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 126s - loss: 1.7784 - acc: 0.4653 - val_loss: 1.8557 - val_acc: 0.4527
{'loss': [1.7784141324802474], 'val_loss': [1.8557002012078652], 'val_acc': [0.45265603928144926], 'acc': [0.46532252167439253]}
Best model so far. Saving...
Iteration Number 6
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 126s - loss: 1.7847 - acc: 0.4628 - val_loss: 1.8586 - val_acc: 0.4410
{'loss': [1.7846633974039814], 'val_loss': [1.8585551615591531], 'val_acc': [0.44098864137118093], 'acc': [0.46277533576589941]}
Iteration Number 7
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 1.7759 - acc: 0.4651 - val_loss: 1.8238 - val_acc: 0.4534
{'loss': [1.7758516026570677], 'val_loss': [1.8238244905960579], 'val_acc': [0.45335478313450894], 'acc': [0.46511939680086128]}
Best model so far. Saving...
Iteration Number 8
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 1.7696 - acc: 0.4666 - val_loss: 1.8281 - val_acc: 0.4523
{'loss': [1.7696031803334209], 'val_loss': [1.8280829694010388], 'val_acc': [0.45228229253672031], 'acc': [0.46656564589695559]}
Iteration Number 9
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 1.7725 - acc: 0.4650 - val_loss: 1.9146 - val_acc: 0.4257
{'loss': [1.7725484031418923], 'val_loss': [1.9146070432383242], 'val_acc': [0.42568127531208683], 'acc': [0.4649568969024237]}
Iteration Number 10
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 2.2777 - acc: 0.3636 - val_loss: 3.0995 - val_acc: 0.1672
{'loss': [2.2776571070813665], 'val_loss': [3.099470085255374], 'val_acc': [0.16716228732683802], 'acc': [0.36355696027696038]}
Iteration Number 11
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 2.9986 - acc: 0.1759 - val_loss: 3.1299 - val_acc: 0.1311
{'loss': [2.9986159508334285], 'val_loss': [3.1298601348325072], 'val_acc': [0.13105510327220496], 'acc': [0.17589801506386166]}
Iteration Number 12
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.0718 - acc: 0.1551 - val_loss: 3.1140 - val_acc: 0.1380
{'loss': [3.0717899839736496], 'val_loss': [3.113994999127458], 'val_acc': [0.13801004241043391], 'acc': [0.15510615305871486]}
Iteration Number 13
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1059 - acc: 0.1454 - val_loss: 3.2156 - val_acc: 0.1476
{'loss': [3.1058742352267013], 'val_loss': [3.2155643729428705], 'val_acc': [0.14758120865667565], 'acc': [0.14540490912241608]}
Iteration Number 14
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1149 - acc: 0.1423 - val_loss: 3.3227 - val_acc: 0.1225
{'loss': [3.1149431244293742], 'val_loss': [3.322720031820106], 'val_acc': [0.12247517834049451], 'acc': [0.1422686610822079]}
Iteration Number 15
Train on 246154 samples, validate on 61539 samples<commit_msg>gru experiment<commit_after>ubuntu@ip-172-31-40-7:~/Text_Generation/code$ cat log_gru.txt
Dataset: ../datasets/poems.txt
corpus length: 923118
total chars: 69
nb sequences: 307693
Vectorization...
Build model...
Iteration Number 1
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 126s - loss: 2.0206 - acc: 0.4054 - val_loss: 1.9534 - val_acc: 0.4136
{'loss': [2.0205905763375553], 'val_loss': [1.9533537864437105], 'val_acc': [0.41355888136511521], 'acc': [0.4054453715967638]}
Best model so far. Saving...
Iteration Number 2
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 127s - loss: 1.8496 - acc: 0.4467 - val_loss: 1.8733 - val_acc: 0.4391
{'loss': [1.8495901757384132], 'val_loss': [1.8733049845830707], 'val_acc': [0.4391199077226004], 'acc': [0.44665128334319004]}
Best model so far. Saving...
Iteration Number 3
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 127s - loss: 1.8109 - acc: 0.4574 - val_loss: 1.8950 - val_acc: 0.4417
{'loss': [1.8108753433806901], 'val_loss': [1.8950475768107411], 'val_acc': [0.44170363509706723], 'acc': [0.45741283911794411]}
Iteration Number 4
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 127s - loss: 1.7965 - acc: 0.4598 - val_loss: 1.8726 - val_acc: 0.4360
{'loss': [1.7964830875350237], 'val_loss': [1.8725598065276123], 'val_acc': [0.4360161848608039], 'acc': [0.45978127513670303]}
Best model so far. Saving...
Iteration Number 5
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 126s - loss: 1.7784 - acc: 0.4653 - val_loss: 1.8557 - val_acc: 0.4527
{'loss': [1.7784141324802474], 'val_loss': [1.8557002012078652], 'val_acc': [0.45265603928144926], 'acc': [0.46532252167439253]}
Best model so far. Saving...
Iteration Number 6
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 126s - loss: 1.7847 - acc: 0.4628 - val_loss: 1.8586 - val_acc: 0.4410
{'loss': [1.7846633974039814], 'val_loss': [1.8585551615591531], 'val_acc': [0.44098864137118093], 'acc': [0.46277533576589941]}
Iteration Number 7
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 1.7759 - acc: 0.4651 - val_loss: 1.8238 - val_acc: 0.4534
{'loss': [1.7758516026570677], 'val_loss': [1.8238244905960579], 'val_acc': [0.45335478313450894], 'acc': [0.46511939680086128]}
Best model so far. Saving...
Iteration Number 8
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 1.7696 - acc: 0.4666 - val_loss: 1.8281 - val_acc: 0.4523
{'loss': [1.7696031803334209], 'val_loss': [1.8280829694010388], 'val_acc': [0.45228229253672031], 'acc': [0.46656564589695559]}
Iteration Number 9
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 1.7725 - acc: 0.4650 - val_loss: 1.9146 - val_acc: 0.4257
{'loss': [1.7725484031418923], 'val_loss': [1.9146070432383242], 'val_acc': [0.42568127531208683], 'acc': [0.4649568969024237]}
Iteration Number 10
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 2.2777 - acc: 0.3636 - val_loss: 3.0995 - val_acc: 0.1672
{'loss': [2.2776571070813665], 'val_loss': [3.099470085255374], 'val_acc': [0.16716228732683802], 'acc': [0.36355696027696038]}
Iteration Number 11
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 2.9986 - acc: 0.1759 - val_loss: 3.1299 - val_acc: 0.1311
{'loss': [2.9986159508334285], 'val_loss': [3.1298601348325072], 'val_acc': [0.13105510327220496], 'acc': [0.17589801506386166]}
Iteration Number 12
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.0718 - acc: 0.1551 - val_loss: 3.1140 - val_acc: 0.1380
{'loss': [3.0717899839736496], 'val_loss': [3.113994999127458], 'val_acc': [0.13801004241043391], 'acc': [0.15510615305871486]}
Iteration Number 13
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1059 - acc: 0.1454 - val_loss: 3.2156 - val_acc: 0.1476
{'loss': [3.1058742352267013], 'val_loss': [3.2155643729428705], 'val_acc': [0.14758120865667565], 'acc': [0.14540490912241608]}
Iteration Number 14
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1149 - acc: 0.1423 - val_loss: 3.3227 - val_acc: 0.1225
{'loss': [3.1149431244293742], 'val_loss': [3.322720031820106], 'val_acc': [0.12247517834049451], 'acc': [0.1422686610822079]}
Iteration Number 15
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1243 - acc: 0.1394 - val_loss: 3.4969 - val_acc: 0.1525
{'loss': [3.1242526462783857], 'val_loss': [3.496890210696999], 'val_acc': [0.15248866573289202], 'acc': [0.13937616288989818]}
Iteration Number 16
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1265 - acc: 0.1383 - val_loss: 3.2357 - val_acc: 0.1518
{'loss': [3.1265062416202372], 'val_loss': [3.2357043506253049], 'val_acc': [0.15175742211626075], 'acc': [0.13833210104267898]}
Iteration Number 17
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1365 - acc: 0.1373 - val_loss: 3.4537 - val_acc: 0.0952
{'loss': [3.1364883272389266], 'val_loss': [3.4537164467036869], 'val_acc': [0.095224166791446296], 'acc': [0.1373042891848798]}
Iteration Number 18
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1372 - acc: 0.1359 - val_loss: 3.3082 - val_acc: 0.1214
{'loss': [3.1372437415897885], 'val_loss': [3.3081949139871827], 'val_acc': [0.1214026877218817], 'acc': [0.13594335253588896]}
Iteration Number 19
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1272 - acc: 0.1391 - val_loss: 3.2282 - val_acc: 0.0913
{'loss': [3.1271744902648817], 'val_loss': [3.2281873672597676], 'val_acc': [0.091291701198946307], 'acc': [0.13908772557017152]}
Iteration Number 20
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1287 - acc: 0.1390 - val_loss: 3.1866 - val_acc: 0.1115
{'loss': [3.1286993690265299], 'val_loss': [3.1865529692241386], 'val_acc': [0.11147402459768403], 'acc': [0.13898616313370857]}
Iteration Number 21
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1312 - acc: 0.1387 - val_loss: 3.2039 - val_acc: 0.1196
{'loss': [3.1312293839559064], 'val_loss': [3.2039178932671404], 'val_acc': [0.11959895350891465], 'acc': [0.13874647578351318]}
Iteration Number 22
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1475 - acc: 0.1352 - val_loss: 3.3752 - val_acc: 0.0939
{'loss': [3.1474662761781524], 'val_loss': [3.3752141779544078], 'val_acc': [0.093940428024160513], 'acc': [0.13516335302302543]}
Iteration Number 23
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1506 - acc: 0.1361 - val_loss: 3.2450 - val_acc: 0.1132
{'loss': [3.1505656522308114], 'val_loss': [3.2449536148043023], 'val_acc': [0.11322900923696771], 'acc': [0.136126164921268]}
Iteration Number 24
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1488 - acc: 0.1358 - val_loss: 3.3074 - val_acc: 0.1163
{'loss': [3.1487562733617378], 'val_loss': [3.3074292053002661], 'val_acc': [0.11634898194471298], 'acc': [0.13578897763194953]}
Iteration Number 25
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1494 - acc: 0.1363 - val_loss: 3.2354 - val_acc: 0.1236
{'loss': [3.1493840432342752], 'val_loss': [3.2353928434067925], 'val_acc': [0.12361266838600375], 'acc': [0.1363374147891763]}
Iteration Number 26
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1497 - acc: 0.1356 - val_loss: 3.3379 - val_acc: 0.1183
{'loss': [3.1496841838325604], 'val_loss': [3.3378950334404611], 'val_acc': [0.11826646516976155], 'acc': [0.13559804025128538]}
Iteration Number 27
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1509 - acc: 0.1351 - val_loss: 3.2221 - val_acc: 0.0975
{'loss': [3.150928995766328], 'val_loss': [3.2221130931684834], 'val_acc': [0.097466647166716214], 'acc': [0.13506179058638088]}
Iteration Number 28
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1508 - acc: 0.1355 - val_loss: 3.3181 - val_acc: 0.0889
{'loss': [3.1507862736243797], 'val_loss': [3.318094183210452], 'val_acc': [0.08887047237416526], 'acc': [0.13545179034275212]}
Iteration Number 29
Train on 246154 samples, validate on 61539 samples
Epoch 1/1
246154/246154 [==============================] - 125s - loss: 3.1535 - acc: 0.1350 - val_loss: 3.2686 - val_acc: 0.1132
{'loss': [3.1534509039467959], 'val_loss': [3.2686350099944237], 'val_acc': [0.11316400982217838], 'acc': [0.13501710311443163]}
{'fraction_non_alphanumeric': 0.2283380206240793, 'fraction_numerical': 0.34679255390384356, 'mean_word_length': 5.204819277108434, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '1039832', 'n_tokens_mistral': 9037, 'n_tokens_neox': 5760, 'n_words': 1428}