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hamedkhaledi
/
persian-flair-pos

Token Classification
Flair
PyTorch
Persian
sequence-tagger-model
Model card Files Community
hamedkhaledi commited on
Commit
fc8375b
•
1 Parent(s): 816ca68

Update model

Browse files
Files changed (3) hide show
  1. loss.tsv +25 -10
  2. pytorch_model.bin +2 -2
  3. training.log +427 -504
loss.tsv CHANGED
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  EPOCH TIMESTAMP BAD_EPOCHS LEARNING_RATE TRAIN_LOSS
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training.log CHANGED
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1
- 2022-08-06 15:12:29,180 ----------------------------------------------------------------------------------------------------
2
- 2022-08-06 15:12:29,182 Model: "SequenceTagger(
3
- (embeddings): TransformerWordEmbeddings(
4
- (model): BertModel(
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- (embeddings): BertEmbeddings(
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- (word_embeddings): Embedding(42000, 768, padding_idx=0)
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- (intermediate_act_fn): GELUActivation()
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- (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
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- (intermediate): BertIntermediate(
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- (dense): Linear(in_features=3072, out_features=768, bias=True)
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- )
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- (output): BertOutput(
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- (dropout): Dropout(p=0.1, inplace=False)
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- (pooler): BertPooler(
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- (dense): Linear(in_features=768, out_features=768, bias=True)
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- (activation): Tanh()
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  )
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  )
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  )
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  (word_dropout): WordDropout(p=0.05)
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  (locked_dropout): LockedDropout(p=0.5)
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- (rnn): LSTM(768, 512, batch_first=True, bidirectional=True)
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  (linear): Linear(in_features=1024, out_features=30, bias=True)
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  (beta): 1.0
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  (weights): None
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  (weight_tensor) None
317
  )"
318
- 2022-08-06 15:12:29,182 ----------------------------------------------------------------------------------------------------
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- 2022-08-06 15:12:29,183 Corpus: "Corpus: 24000 train + 3000 dev + 3000 test sentences"
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- 2022-08-06 15:12:29,183 ----------------------------------------------------------------------------------------------------
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- 2022-08-06 15:12:29,183 Parameters:
322
- 2022-08-06 15:12:29,183 - learning_rate: "0.1"
323
- 2022-08-06 15:12:29,183 - mini_batch_size: "8"
324
- 2022-08-06 15:12:29,183 - patience: "3"
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- 2022-08-06 15:12:29,183 - anneal_factor: "0.5"
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- 2022-08-06 15:12:29,183 - max_epochs: "10"
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- 2022-08-06 15:12:29,183 - shuffle: "True"
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- 2022-08-06 15:12:29,183 - train_with_dev: "True"
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- 2022-08-06 15:12:29,183 - batch_growth_annealing: "False"
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- 2022-08-06 15:12:29,183 ----------------------------------------------------------------------------------------------------
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- 2022-08-06 15:12:29,183 Model training base path: "data/pos-Uppsala/model"
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- 2022-08-06 15:12:29,183 ----------------------------------------------------------------------------------------------------
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- 2022-08-06 15:12:29,183 Device: cuda:0
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- 2022-08-06 15:12:29,183 ----------------------------------------------------------------------------------------------------
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- 2022-08-06 15:12:29,184 Embeddings storage mode: gpu
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- 2022-08-06 15:12:29,185 ----------------------------------------------------------------------------------------------------
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- 2022-08-06 15:13:18,972 epoch 1 - iter 337/3375 - loss 0.74289984 - samples/sec: 54.18 - lr: 0.100000
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- 2022-08-06 15:14:15,036 epoch 1 - iter 674/3375 - loss 0.53599298 - samples/sec: 48.11 - lr: 0.100000
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- 2022-08-06 15:15:12,610 epoch 1 - iter 1011/3375 - loss 0.45754038 - samples/sec: 46.85 - lr: 0.100000
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- 2022-08-06 15:16:09,043 epoch 1 - iter 1348/3375 - loss 0.40111208 - samples/sec: 47.79 - lr: 0.100000
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- 2022-08-06 15:17:04,137 epoch 1 - iter 1685/3375 - loss 0.36712663 - samples/sec: 48.96 - lr: 0.100000
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- 2022-08-06 15:17:58,402 epoch 1 - iter 2022/3375 - loss 0.34049225 - samples/sec: 49.70 - lr: 0.100000
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- 2022-08-06 15:18:55,276 epoch 1 - iter 2359/3375 - loss 0.32076226 - samples/sec: 47.42 - lr: 0.100000
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- 2022-08-06 15:19:49,979 epoch 1 - iter 2696/3375 - loss 0.31015506 - samples/sec: 49.31 - lr: 0.100000
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- 2022-08-06 15:20:48,410 epoch 1 - iter 3033/3375 - loss 0.29391699 - samples/sec: 46.16 - lr: 0.100000
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- 2022-08-06 15:21:47,572 epoch 1 - iter 3370/3375 - loss 0.27989028 - samples/sec: 45.59 - lr: 0.100000
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- 2022-08-06 15:21:48,555 ----------------------------------------------------------------------------------------------------
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- 2022-08-06 15:21:48,555 EPOCH 1 done: loss 0.2795 - lr 0.1000000
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- 2022-08-06 15:21:48,555 BAD EPOCHS (no improvement): 0
350
- 2022-08-06 15:21:48,555 ----------------------------------------------------------------------------------------------------
351
- 2022-08-06 15:22:45,590 epoch 2 - iter 337/3375 - loss 0.18085661 - samples/sec: 47.29 - lr: 0.100000
352
- 2022-08-06 15:23:42,698 epoch 2 - iter 674/3375 - loss 0.17216272 - samples/sec: 47.23 - lr: 0.100000
353
- 2022-08-06 15:24:38,534 epoch 2 - iter 1011/3375 - loss 0.16694117 - samples/sec: 48.31 - lr: 0.100000
354
- 2022-08-06 15:25:36,464 epoch 2 - iter 1348/3375 - loss 0.16500505 - samples/sec: 46.56 - lr: 0.100000
355
- 2022-08-06 15:26:32,174 epoch 2 - iter 1685/3375 - loss 0.16167195 - samples/sec: 48.42 - lr: 0.100000
356
- 2022-08-06 15:27:28,418 epoch 2 - iter 2022/3375 - loss 0.15991464 - samples/sec: 47.96 - lr: 0.100000
357
- 2022-08-06 15:28:30,730 epoch 2 - iter 2359/3375 - loss 0.15942296 - samples/sec: 43.29 - lr: 0.100000
358
- 2022-08-06 15:29:27,444 epoch 2 - iter 2696/3375 - loss 0.15779417 - samples/sec: 47.56 - lr: 0.100000
359
- 2022-08-06 15:30:25,187 epoch 2 - iter 3033/3375 - loss 0.15553239 - samples/sec: 46.71 - lr: 0.100000
360
- 2022-08-06 15:31:21,714 epoch 2 - iter 3370/3375 - loss 0.15352182 - samples/sec: 47.72 - lr: 0.100000
361
- 2022-08-06 15:31:22,712 ----------------------------------------------------------------------------------------------------
362
- 2022-08-06 15:31:22,712 EPOCH 2 done: loss 0.1537 - lr 0.1000000
363
- 2022-08-06 15:31:22,712 BAD EPOCHS (no improvement): 0
364
- 2022-08-06 15:31:22,712 ----------------------------------------------------------------------------------------------------
365
- 2022-08-06 15:32:23,790 epoch 3 - iter 337/3375 - loss 0.11867195 - samples/sec: 44.16 - lr: 0.100000
366
- 2022-08-06 15:33:21,161 epoch 3 - iter 674/3375 - loss 0.11878234 - samples/sec: 47.02 - lr: 0.100000
367
- 2022-08-06 15:34:20,702 epoch 3 - iter 1011/3375 - loss 0.11942785 - samples/sec: 45.31 - lr: 0.100000
368
- 2022-08-06 15:35:18,259 epoch 3 - iter 1348/3375 - loss 0.11958903 - samples/sec: 46.86 - lr: 0.100000
369
- 2022-08-06 15:36:16,967 epoch 3 - iter 1685/3375 - loss 0.11914369 - samples/sec: 45.94 - lr: 0.100000
370
- 2022-08-06 15:37:13,560 epoch 3 - iter 2022/3375 - loss 0.11916365 - samples/sec: 47.66 - lr: 0.100000
371
- 2022-08-06 15:38:10,624 epoch 3 - iter 2359/3375 - loss 0.12096981 - samples/sec: 47.27 - lr: 0.100000
372
- 2022-08-06 15:39:10,034 epoch 3 - iter 2696/3375 - loss 0.11987245 - samples/sec: 45.40 - lr: 0.100000
373
- 2022-08-06 15:40:07,877 epoch 3 - iter 3033/3375 - loss 0.11973164 - samples/sec: 46.63 - lr: 0.100000
374
- 2022-08-06 15:41:05,610 epoch 3 - iter 3370/3375 - loss 0.12003917 - samples/sec: 46.72 - lr: 0.100000
375
- 2022-08-06 15:41:06,450 ----------------------------------------------------------------------------------------------------
376
- 2022-08-06 15:41:06,450 EPOCH 3 done: loss 0.1200 - lr 0.1000000
377
- 2022-08-06 15:41:06,450 BAD EPOCHS (no improvement): 0
378
- 2022-08-06 15:41:06,451 ----------------------------------------------------------------------------------------------------
379
- 2022-08-06 15:42:04,442 epoch 4 - iter 337/3375 - loss 0.09805702 - samples/sec: 46.51 - lr: 0.100000
380
- 2022-08-06 15:43:05,164 epoch 4 - iter 674/3375 - loss 0.09888569 - samples/sec: 44.42 - lr: 0.100000
381
- 2022-08-06 15:44:02,546 epoch 4 - iter 1011/3375 - loss 0.10053644 - samples/sec: 47.01 - lr: 0.100000
382
- 2022-08-06 15:45:01,384 epoch 4 - iter 1348/3375 - loss 0.10119574 - samples/sec: 45.84 - lr: 0.100000
383
- 2022-08-06 15:46:00,229 epoch 4 - iter 1685/3375 - loss 0.10374826 - samples/sec: 45.84 - lr: 0.100000
384
- 2022-08-06 15:46:59,791 epoch 4 - iter 2022/3375 - loss 0.10405522 - samples/sec: 45.28 - lr: 0.100000
385
- 2022-08-06 15:47:57,607 epoch 4 - iter 2359/3375 - loss 0.10411718 - samples/sec: 46.65 - lr: 0.100000
386
- 2022-08-06 15:48:55,410 epoch 4 - iter 2696/3375 - loss 0.10394934 - samples/sec: 46.66 - lr: 0.100000
387
- 2022-08-06 15:49:56,783 epoch 4 - iter 3033/3375 - loss 0.10374714 - samples/sec: 43.95 - lr: 0.100000
388
- 2022-08-06 15:50:54,113 epoch 4 - iter 3370/3375 - loss 0.10333066 - samples/sec: 47.05 - lr: 0.100000
389
- 2022-08-06 15:50:54,961 ----------------------------------------------------------------------------------------------------
390
- 2022-08-06 15:50:54,961 EPOCH 4 done: loss 0.1033 - lr 0.1000000
391
- 2022-08-06 15:50:54,961 BAD EPOCHS (no improvement): 0
392
- 2022-08-06 15:50:54,961 ----------------------------------------------------------------------------------------------------
393
- 2022-08-06 15:51:52,151 epoch 5 - iter 337/3375 - loss 0.08744228 - samples/sec: 47.17 - lr: 0.100000
394
- 2022-08-06 15:52:49,910 epoch 5 - iter 674/3375 - loss 0.08896766 - samples/sec: 46.70 - lr: 0.100000
395
- 2022-08-06 15:53:50,861 epoch 5 - iter 1011/3375 - loss 0.09000325 - samples/sec: 44.25 - lr: 0.100000
396
- 2022-08-06 15:54:48,357 epoch 5 - iter 1348/3375 - loss 0.09103779 - samples/sec: 46.91 - lr: 0.100000
397
- 2022-08-06 15:55:48,122 epoch 5 - iter 1685/3375 - loss 0.09107958 - samples/sec: 45.13 - lr: 0.100000
398
- 2022-08-06 15:56:49,324 epoch 5 - iter 2022/3375 - loss 0.09135469 - samples/sec: 44.07 - lr: 0.100000
399
- 2022-08-06 15:57:47,393 epoch 5 - iter 2359/3375 - loss 0.09172710 - samples/sec: 46.45 - lr: 0.100000
400
- 2022-08-06 15:58:45,694 epoch 5 - iter 2696/3375 - loss 0.09238154 - samples/sec: 46.27 - lr: 0.100000
401
- 2022-08-06 15:59:42,885 epoch 5 - iter 3033/3375 - loss 0.09253470 - samples/sec: 47.16 - lr: 0.100000
402
- 2022-08-06 16:00:44,492 epoch 5 - iter 3370/3375 - loss 0.09240350 - samples/sec: 43.78 - lr: 0.100000
403
- 2022-08-06 16:00:45,327 ----------------------------------------------------------------------------------------------------
404
- 2022-08-06 16:00:45,328 EPOCH 5 done: loss 0.0924 - lr 0.1000000
405
- 2022-08-06 16:00:45,328 BAD EPOCHS (no improvement): 0
406
- 2022-08-06 16:00:45,328 ----------------------------------------------------------------------------------------------------
407
- 2022-08-06 16:01:42,167 epoch 6 - iter 337/3375 - loss 0.08075428 - samples/sec: 47.46 - lr: 0.100000
408
- 2022-08-06 16:02:39,509 epoch 6 - iter 674/3375 - loss 0.08099115 - samples/sec: 47.04 - lr: 0.100000
409
- 2022-08-06 16:03:37,688 epoch 6 - iter 1011/3375 - loss 0.08140463 - samples/sec: 46.36 - lr: 0.100000
410
- 2022-08-06 16:04:38,640 epoch 6 - iter 1348/3375 - loss 0.08175190 - samples/sec: 44.25 - lr: 0.100000
411
- 2022-08-06 16:05:35,459 epoch 6 - iter 1685/3375 - loss 0.08233525 - samples/sec: 47.47 - lr: 0.100000
412
- 2022-08-06 16:06:33,941 epoch 6 - iter 2022/3375 - loss 0.08333964 - samples/sec: 46.12 - lr: 0.100000
413
- 2022-08-06 16:07:34,247 epoch 6 - iter 2359/3375 - loss 0.08370656 - samples/sec: 44.73 - lr: 0.100000
414
- 2022-08-06 16:08:32,546 epoch 6 - iter 2696/3375 - loss 0.08503503 - samples/sec: 46.27 - lr: 0.100000
415
- 2022-08-06 16:09:30,447 epoch 6 - iter 3033/3375 - loss 0.08526801 - samples/sec: 46.58 - lr: 0.100000
416
- 2022-08-06 16:10:29,216 epoch 6 - iter 3370/3375 - loss 0.08506276 - samples/sec: 45.90 - lr: 0.100000
417
- 2022-08-06 16:10:29,946 ----------------------------------------------------------------------------------------------------
418
- 2022-08-06 16:10:29,947 EPOCH 6 done: loss 0.0851 - lr 0.1000000
419
- 2022-08-06 16:10:29,947 BAD EPOCHS (no improvement): 0
420
- 2022-08-06 16:10:29,947 ----------------------------------------------------------------------------------------------------
421
- 2022-08-06 16:11:31,042 epoch 7 - iter 337/3375 - loss 0.07328964 - samples/sec: 44.15 - lr: 0.100000
422
- 2022-08-06 16:12:31,218 epoch 7 - iter 674/3375 - loss 0.07556648 - samples/sec: 44.82 - lr: 0.100000
423
- 2022-08-06 16:13:28,468 epoch 7 - iter 1011/3375 - loss 0.07578294 - samples/sec: 47.11 - lr: 0.100000
424
- 2022-08-06 16:14:28,318 epoch 7 - iter 1348/3375 - loss 0.07581855 - samples/sec: 45.07 - lr: 0.100000
425
- 2022-08-06 16:15:27,119 epoch 7 - iter 1685/3375 - loss 0.07674717 - samples/sec: 45.87 - lr: 0.100000
426
- 2022-08-06 16:16:25,205 epoch 7 - iter 2022/3375 - loss 0.07800463 - samples/sec: 46.44 - lr: 0.100000
427
- 2022-08-06 16:17:25,635 epoch 7 - iter 2359/3375 - loss 0.07788540 - samples/sec: 44.64 - lr: 0.100000
428
- 2022-08-06 16:18:25,934 epoch 7 - iter 2696/3375 - loss 0.07823310 - samples/sec: 44.73 - lr: 0.100000
429
- 2022-08-06 16:19:25,742 epoch 7 - iter 3033/3375 - loss 0.07862489 - samples/sec: 45.10 - lr: 0.100000
430
- 2022-08-06 16:20:24,514 epoch 7 - iter 3370/3375 - loss 0.07864779 - samples/sec: 45.89 - lr: 0.100000
431
- 2022-08-06 16:20:25,316 ----------------------------------------------------------------------------------------------------
432
- 2022-08-06 16:20:25,317 EPOCH 7 done: loss 0.0786 - lr 0.1000000
433
- 2022-08-06 16:20:25,317 BAD EPOCHS (no improvement): 0
434
- 2022-08-06 16:20:25,317 ----------------------------------------------------------------------------------------------------
435
- 2022-08-06 16:21:23,040 epoch 8 - iter 337/3375 - loss 0.06876001 - samples/sec: 46.73 - lr: 0.100000
436
- 2022-08-06 16:22:25,028 epoch 8 - iter 674/3375 - loss 0.06867038 - samples/sec: 43.51 - lr: 0.100000
437
- 2022-08-06 16:23:25,046 epoch 8 - iter 1011/3375 - loss 0.07011779 - samples/sec: 44.94 - lr: 0.100000
438
- 2022-08-06 16:24:23,287 epoch 8 - iter 1348/3375 - loss 0.07118411 - samples/sec: 46.31 - lr: 0.100000
439
- 2022-08-06 16:25:24,939 epoch 8 - iter 1685/3375 - loss 0.07159055 - samples/sec: 43.75 - lr: 0.100000
440
- 2022-08-06 16:26:23,316 epoch 8 - iter 2022/3375 - loss 0.07167687 - samples/sec: 46.21 - lr: 0.100000
441
- 2022-08-06 16:27:22,234 epoch 8 - iter 2359/3375 - loss 0.07190781 - samples/sec: 45.78 - lr: 0.100000
442
- 2022-08-06 16:28:20,921 epoch 8 - iter 2696/3375 - loss 0.07263123 - samples/sec: 45.96 - lr: 0.100000
443
- 2022-08-06 16:29:21,637 epoch 8 - iter 3033/3375 - loss 0.07345723 - samples/sec: 44.42 - lr: 0.100000
444
- 2022-08-06 16:30:20,403 epoch 8 - iter 3370/3375 - loss 0.07338627 - samples/sec: 45.90 - lr: 0.100000
445
- 2022-08-06 16:30:21,375 ----------------------------------------------------------------------------------------------------
446
- 2022-08-06 16:30:21,375 EPOCH 8 done: loss 0.0734 - lr 0.1000000
447
- 2022-08-06 16:30:21,375 BAD EPOCHS (no improvement): 0
448
- 2022-08-06 16:30:21,376 ----------------------------------------------------------------------------------------------------
449
- 2022-08-06 16:31:18,803 epoch 9 - iter 337/3375 - loss 0.06314787 - samples/sec: 46.97 - lr: 0.100000
450
- 2022-08-06 16:32:16,661 epoch 9 - iter 674/3375 - loss 0.06638022 - samples/sec: 46.62 - lr: 0.100000
451
- 2022-08-06 16:33:15,745 epoch 9 - iter 1011/3375 - loss 0.06547021 - samples/sec: 45.65 - lr: 0.100000
452
- 2022-08-06 16:34:14,632 epoch 9 - iter 1348/3375 - loss 0.06593581 - samples/sec: 45.81 - lr: 0.100000
453
- 2022-08-06 16:35:13,668 epoch 9 - iter 1685/3375 - loss 0.06772817 - samples/sec: 45.69 - lr: 0.100000
454
- 2022-08-06 16:36:15,567 epoch 9 - iter 2022/3375 - loss 0.06808051 - samples/sec: 43.58 - lr: 0.100000
455
- 2022-08-06 16:37:16,651 epoch 9 - iter 2359/3375 - loss 0.06796916 - samples/sec: 44.16 - lr: 0.100000
456
- 2022-08-06 16:38:14,513 epoch 9 - iter 2696/3375 - loss 0.06906572 - samples/sec: 46.62 - lr: 0.100000
457
- 2022-08-06 16:39:13,107 epoch 9 - iter 3033/3375 - loss 0.06917054 - samples/sec: 46.03 - lr: 0.100000
458
- 2022-08-06 16:40:12,475 epoch 9 - iter 3370/3375 - loss 0.06913866 - samples/sec: 45.43 - lr: 0.100000
459
- 2022-08-06 16:40:13,344 ----------------------------------------------------------------------------------------------------
460
- 2022-08-06 16:40:13,344 EPOCH 9 done: loss 0.0691 - lr 0.1000000
461
- 2022-08-06 16:40:13,344 BAD EPOCHS (no improvement): 0
462
- 2022-08-06 16:40:13,345 ----------------------------------------------------------------------------------------------------
463
- 2022-08-06 16:41:11,629 epoch 10 - iter 337/3375 - loss 0.05727560 - samples/sec: 46.28 - lr: 0.100000
464
- 2022-08-06 16:42:09,047 epoch 10 - iter 674/3375 - loss 0.06063155 - samples/sec: 46.98 - lr: 0.100000
465
- 2022-08-06 16:43:09,515 epoch 10 - iter 1011/3375 - loss 0.06369582 - samples/sec: 44.61 - lr: 0.100000
466
- 2022-08-06 16:44:07,978 epoch 10 - iter 1348/3375 - loss 0.06421773 - samples/sec: 46.14 - lr: 0.100000
467
- 2022-08-06 16:45:07,015 epoch 10 - iter 1685/3375 - loss 0.06397856 - samples/sec: 45.69 - lr: 0.100000
468
- 2022-08-06 16:46:05,736 epoch 10 - iter 2022/3375 - loss 0.06424947 - samples/sec: 45.93 - lr: 0.100000
469
- 2022-08-06 16:47:06,945 epoch 10 - iter 2359/3375 - loss 0.06511606 - samples/sec: 44.07 - lr: 0.100000
470
- 2022-08-06 16:48:05,819 epoch 10 - iter 2696/3375 - loss 0.06574495 - samples/sec: 45.82 - lr: 0.100000
471
- 2022-08-06 16:49:03,924 epoch 10 - iter 3033/3375 - loss 0.06552271 - samples/sec: 46.42 - lr: 0.100000
472
- 2022-08-06 16:50:00,641 epoch 10 - iter 3370/3375 - loss 0.06594147 - samples/sec: 47.56 - lr: 0.100000
473
- 2022-08-06 16:50:01,493 ----------------------------------------------------------------------------------------------------
474
- 2022-08-06 16:50:01,493 EPOCH 10 done: loss 0.0659 - lr 0.1000000
475
- 2022-08-06 16:50:01,493 BAD EPOCHS (no improvement): 0
476
- 2022-08-06 16:50:02,708 ----------------------------------------------------------------------------------------------------
477
- 2022-08-06 16:50:02,709 Testing using last state of model ...
478
- 2022-08-06 16:53:40,214 0.9632 0.9632 0.9632 0.9632
479
- 2022-08-06 16:53:40,215
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
480
  Results:
481
- - F-score (micro) 0.9632
482
- - F-score (macro) 0.9031
483
- - Accuracy 0.9632
484
 
485
  By class:
486
  precision recall f1-score support
487
 
488
- N_SING 0.9691 0.9565 0.9627 30553
489
- P 0.9560 0.9937 0.9745 9951
490
- DELM 0.9936 0.9906 0.9921 8122
491
- ADJ 0.9205 0.9152 0.9179 7466
492
- CON 0.9892 0.9799 0.9845 6823
493
- N_PL 0.9476 0.9642 0.9558 5163
494
- V_PA 0.9729 0.9746 0.9737 2873
495
- V_PRS 0.9825 0.9898 0.9861 2841
496
- PRO 0.9656 0.9455 0.9555 2258
497
- NUM 0.9937 0.9933 0.9935 2232
498
- DET 0.9423 0.9698 0.9559 1853
499
- CLITIC 0.9992 1.0000 0.9996 1259
500
- V_PP 0.9699 0.9741 0.9720 1158
501
- V_SUB 0.9620 0.9573 0.9596 1031
502
- ADV 0.7784 0.8182 0.7978 880
503
- ADV_TIME 0.9126 0.9611 0.9363 489
504
- V_AUX 0.9869 0.9974 0.9921 379
505
- ADJ_SUP 0.9851 0.9815 0.9833 270
506
- ADJ_CMPR 0.9246 0.9534 0.9388 193
507
- ADJ_INO 0.7294 0.7381 0.7337 168
508
- ADV_NEG 0.9034 0.8792 0.8912 149
509
- ADV_I 0.8926 0.7714 0.8276 140
510
- FW 0.6893 0.5772 0.6283 123
511
- ADV_COMP 0.8267 0.8158 0.8212 76
512
- ADV_LOC 0.9722 0.9589 0.9655 73
513
- V_IMP 0.7292 0.6250 0.6731 56
514
- PREV 0.9286 0.8125 0.8667 32
515
- INT 0.9231 0.5000 0.6486 24
 
516
 
517
- micro avg 0.9632 0.9632 0.9632 86635
518
- macro avg 0.9195 0.8926 0.9031 86635
519
- weighted avg 0.9633 0.9632 0.9631 86635
520
- samples avg 0.9632 0.9632 0.9632 86635
521
 
522
- 2022-08-06 16:53:40,215 ----------------------------------------------------------------------------------------------------
 
1
+ 2022-08-06 17:35:48,202 ----------------------------------------------------------------------------------------------------
2
+ 2022-08-06 17:35:48,202 Model: "SequenceTagger(
3
+ (embeddings): StackedEmbeddings(
4
+ (list_embedding_0): WordEmbeddings('fa')
5
+ (list_embedding_1): FlairEmbeddings(
6
+ (lm): LanguageModel(
7
+ (drop): Dropout(p=0.1, inplace=False)
8
+ (encoder): Embedding(5105, 100)
9
+ (rnn): LSTM(100, 2048)
10
+ (decoder): Linear(in_features=2048, out_features=5105, bias=True)
11
  )
12
+ )
13
+ (list_embedding_2): FlairEmbeddings(
14
+ (lm): LanguageModel(
15
+ (drop): Dropout(p=0.1, inplace=False)
16
+ (encoder): Embedding(5105, 100)
17
+ (rnn): LSTM(100, 2048)
18
+ (decoder): Linear(in_features=2048, out_features=5105, bias=True)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
19
  )
20
  )
21
  )
22
  (word_dropout): WordDropout(p=0.05)
23
  (locked_dropout): LockedDropout(p=0.5)
24
+ (rnn): LSTM(4396, 512, batch_first=True, bidirectional=True)
25
  (linear): Linear(in_features=1024, out_features=30, bias=True)
26
  (beta): 1.0
27
  (weights): None
28
  (weight_tensor) None
29
  )"
30
+ 2022-08-06 17:35:48,203 ----------------------------------------------------------------------------------------------------
31
+ 2022-08-06 17:35:48,203 Corpus: "Corpus: 24000 train + 3000 dev + 3000 test sentences"
32
+ 2022-08-06 17:35:48,203 ----------------------------------------------------------------------------------------------------
33
+ 2022-08-06 17:35:48,203 Parameters:
34
+ 2022-08-06 17:35:48,203 - learning_rate: "0.1"
35
+ 2022-08-06 17:35:48,203 - mini_batch_size: "8"
36
+ 2022-08-06 17:35:48,203 - patience: "3"
37
+ 2022-08-06 17:35:48,203 - anneal_factor: "0.5"
38
+ 2022-08-06 17:35:48,203 - max_epochs: "25"
39
+ 2022-08-06 17:35:48,203 - shuffle: "True"
40
+ 2022-08-06 17:35:48,203 - train_with_dev: "True"
41
+ 2022-08-06 17:35:48,203 - batch_growth_annealing: "False"
42
+ 2022-08-06 17:35:48,203 ----------------------------------------------------------------------------------------------------
43
+ 2022-08-06 17:35:48,203 Model training base path: "data/pos-Uppsala/model2"
44
+ 2022-08-06 17:35:48,203 ----------------------------------------------------------------------------------------------------
45
+ 2022-08-06 17:35:48,203 Device: cuda:0
46
+ 2022-08-06 17:35:48,203 ----------------------------------------------------------------------------------------------------
47
+ 2022-08-06 17:35:48,203 Embeddings storage mode: gpu
48
+ 2022-08-06 17:35:48,204 ----------------------------------------------------------------------------------------------------
49
+ 2022-08-06 17:36:07,702 epoch 1 - iter 337/3375 - loss 0.77290691 - samples/sec: 138.41 - lr: 0.100000
50
+ 2022-08-06 17:36:34,210 epoch 1 - iter 674/3375 - loss 0.55640684 - samples/sec: 101.78 - lr: 0.100000
51
+ 2022-08-06 17:36:57,947 epoch 1 - iter 1011/3375 - loss 0.48188686 - samples/sec: 113.68 - lr: 0.100000
52
+ 2022-08-06 17:37:26,596 epoch 1 - iter 1348/3375 - loss 0.42604018 - samples/sec: 94.17 - lr: 0.100000
53
+ 2022-08-06 17:37:51,571 epoch 1 - iter 1685/3375 - loss 0.39190904 - samples/sec: 108.03 - lr: 0.100000
54
+ 2022-08-06 17:38:15,619 epoch 1 - iter 2022/3375 - loss 0.36624726 - samples/sec: 112.20 - lr: 0.100000
55
+ 2022-08-06 17:38:39,142 epoch 1 - iter 2359/3375 - loss 0.34624083 - samples/sec: 114.72 - lr: 0.100000
56
+ 2022-08-06 17:39:02,810 epoch 1 - iter 2696/3375 - loss 0.33885530 - samples/sec: 113.99 - lr: 0.100000
57
+ 2022-08-06 17:39:28,607 epoch 1 - iter 3033/3375 - loss 0.32396264 - samples/sec: 104.59 - lr: 0.100000
58
+ 2022-08-06 17:39:57,555 epoch 1 - iter 3370/3375 - loss 0.31127943 - samples/sec: 93.19 - lr: 0.100000
59
+ 2022-08-06 17:39:58,067 ----------------------------------------------------------------------------------------------------
60
+ 2022-08-06 17:39:58,067 EPOCH 1 done: loss 0.3110 - lr 0.1000000
61
+ 2022-08-06 17:39:58,067 BAD EPOCHS (no improvement): 0
62
+ 2022-08-06 17:39:58,067 ----------------------------------------------------------------------------------------------------
63
+ 2022-08-06 17:40:03,822 epoch 2 - iter 337/3375 - loss 0.22000243 - samples/sec: 470.89 - lr: 0.100000
64
+ 2022-08-06 17:40:08,271 epoch 2 - iter 674/3375 - loss 0.21810059 - samples/sec: 608.44 - lr: 0.100000
65
+ 2022-08-06 17:40:12,545 epoch 2 - iter 1011/3375 - loss 0.21667145 - samples/sec: 633.25 - lr: 0.100000
66
+ 2022-08-06 17:40:16,752 epoch 2 - iter 1348/3375 - loss 0.21318611 - samples/sec: 643.42 - lr: 0.100000
67
+ 2022-08-06 17:40:20,957 epoch 2 - iter 1685/3375 - loss 0.21031869 - samples/sec: 643.76 - lr: 0.100000
68
+ 2022-08-06 17:40:25,137 epoch 2 - iter 2022/3375 - loss 0.20983332 - samples/sec: 647.48 - lr: 0.100000
69
+ 2022-08-06 17:40:29,599 epoch 2 - iter 2359/3375 - loss 0.20703899 - samples/sec: 606.71 - lr: 0.100000
70
+ 2022-08-06 17:40:34,023 epoch 2 - iter 2696/3375 - loss 0.20541980 - samples/sec: 611.99 - lr: 0.100000
71
+ 2022-08-06 17:40:38,282 epoch 2 - iter 3033/3375 - loss 0.20260610 - samples/sec: 635.82 - lr: 0.100000
72
+ 2022-08-06 17:40:42,609 epoch 2 - iter 3370/3375 - loss 0.20057442 - samples/sec: 625.77 - lr: 0.100000
73
+ 2022-08-06 17:40:42,665 ----------------------------------------------------------------------------------------------------
74
+ 2022-08-06 17:40:42,665 EPOCH 2 done: loss 0.2006 - lr 0.1000000
75
+ 2022-08-06 17:40:42,665 BAD EPOCHS (no improvement): 0
76
+ 2022-08-06 17:40:42,666 ----------------------------------------------------------------------------------------------------
77
+ 2022-08-06 17:40:47,025 epoch 3 - iter 337/3375 - loss 0.17771924 - samples/sec: 621.20 - lr: 0.100000
78
+ 2022-08-06 17:40:51,398 epoch 3 - iter 674/3375 - loss 0.17936778 - samples/sec: 619.19 - lr: 0.100000
79
+ 2022-08-06 17:40:56,125 epoch 3 - iter 1011/3375 - loss 0.18121841 - samples/sec: 572.69 - lr: 0.100000
80
+ 2022-08-06 17:41:00,518 epoch 3 - iter 1348/3375 - loss 0.17922858 - samples/sec: 616.39 - lr: 0.100000
81
+ 2022-08-06 17:41:04,814 epoch 3 - iter 1685/3375 - loss 0.17910916 - samples/sec: 629.94 - lr: 0.100000
82
+ 2022-08-06 17:41:09,164 epoch 3 - iter 2022/3375 - loss 0.17786989 - samples/sec: 622.33 - lr: 0.100000
83
+ 2022-08-06 17:41:13,758 epoch 3 - iter 2359/3375 - loss 0.17680080 - samples/sec: 589.38 - lr: 0.100000
84
+ 2022-08-06 17:41:18,128 epoch 3 - iter 2696/3375 - loss 0.17616815 - samples/sec: 619.46 - lr: 0.100000
85
+ 2022-08-06 17:41:22,541 epoch 3 - iter 3033/3375 - loss 0.17461992 - samples/sec: 613.49 - lr: 0.100000
86
+ 2022-08-06 17:41:27,173 epoch 3 - iter 3370/3375 - loss 0.17265068 - samples/sec: 584.33 - lr: 0.100000
87
+ 2022-08-06 17:41:27,251 ----------------------------------------------------------------------------------------------------
88
+ 2022-08-06 17:41:27,251 EPOCH 3 done: loss 0.1726 - lr 0.1000000
89
+ 2022-08-06 17:41:27,251 BAD EPOCHS (no improvement): 0
90
+ 2022-08-06 17:41:27,251 ----------------------------------------------------------------------------------------------------
91
+ 2022-08-06 17:41:31,673 epoch 4 - iter 337/3375 - loss 0.15437579 - samples/sec: 612.33 - lr: 0.100000
92
+ 2022-08-06 17:41:36,072 epoch 4 - iter 674/3375 - loss 0.15652144 - samples/sec: 615.26 - lr: 0.100000
93
+ 2022-08-06 17:41:40,469 epoch 4 - iter 1011/3375 - loss 0.15490180 - samples/sec: 615.65 - lr: 0.100000
94
+ 2022-08-06 17:41:44,794 epoch 4 - iter 1348/3375 - loss 0.15480884 - samples/sec: 625.89 - lr: 0.100000
95
+ 2022-08-06 17:41:49,059 epoch 4 - iter 1685/3375 - loss 0.15396863 - samples/sec: 634.71 - lr: 0.100000
96
+ 2022-08-06 17:41:53,454 epoch 4 - iter 2022/3375 - loss 0.15340456 - samples/sec: 615.96 - lr: 0.100000
97
+ 2022-08-06 17:41:58,152 epoch 4 - iter 2359/3375 - loss 0.15515344 - samples/sec: 576.18 - lr: 0.100000
98
+ 2022-08-06 17:42:02,284 epoch 4 - iter 2696/3375 - loss 0.15519133 - samples/sec: 655.28 - lr: 0.100000
99
+ 2022-08-06 17:42:06,584 epoch 4 - iter 3033/3375 - loss 0.15564569 - samples/sec: 629.61 - lr: 0.100000
100
+ 2022-08-06 17:42:11,133 epoch 4 - iter 3370/3375 - loss 0.15577193 - samples/sec: 595.04 - lr: 0.100000
101
+ 2022-08-06 17:42:11,209 ----------------------------------------------------------------------------------------------------
102
+ 2022-08-06 17:42:11,209 EPOCH 4 done: loss 0.1558 - lr 0.1000000
103
+ 2022-08-06 17:42:11,209 BAD EPOCHS (no improvement): 0
104
+ 2022-08-06 17:42:11,209 ----------------------------------------------------------------------------------------------------
105
+ 2022-08-06 17:42:15,710 epoch 5 - iter 337/3375 - loss 0.16345933 - samples/sec: 601.61 - lr: 0.100000
106
+ 2022-08-06 17:42:20,321 epoch 5 - iter 674/3375 - loss 0.15117171 - samples/sec: 587.22 - lr: 0.100000
107
+ 2022-08-06 17:42:24,785 epoch 5 - iter 1011/3375 - loss 0.14779631 - samples/sec: 606.48 - lr: 0.100000
108
+ 2022-08-06 17:42:29,011 epoch 5 - iter 1348/3375 - loss 0.14941071 - samples/sec: 640.49 - lr: 0.100000
109
+ 2022-08-06 17:42:33,568 epoch 5 - iter 1685/3375 - loss 0.14817966 - samples/sec: 594.13 - lr: 0.100000
110
+ 2022-08-06 17:42:37,869 epoch 5 - iter 2022/3375 - loss 0.14807553 - samples/sec: 629.20 - lr: 0.100000
111
+ 2022-08-06 17:42:42,062 epoch 5 - iter 2359/3375 - loss 0.14806238 - samples/sec: 645.63 - lr: 0.100000
112
+ 2022-08-06 17:42:46,590 epoch 5 - iter 2696/3375 - loss 0.14768088 - samples/sec: 597.74 - lr: 0.100000
113
+ 2022-08-06 17:42:51,012 epoch 5 - iter 3033/3375 - loss 0.14692530 - samples/sec: 611.95 - lr: 0.100000
114
+ 2022-08-06 17:42:55,435 epoch 5 - iter 3370/3375 - loss 0.14619224 - samples/sec: 612.11 - lr: 0.100000
115
+ 2022-08-06 17:42:55,501 ----------------------------------------------------------------------------------------------------
116
+ 2022-08-06 17:42:55,501 EPOCH 5 done: loss 0.1461 - lr 0.1000000
117
+ 2022-08-06 17:42:55,501 BAD EPOCHS (no improvement): 0
118
+ 2022-08-06 17:42:55,502 ----------------------------------------------------------------------------------------------------
119
+ 2022-08-06 17:43:00,680 epoch 6 - iter 337/3375 - loss 0.12871632 - samples/sec: 523.18 - lr: 0.100000
120
+ 2022-08-06 17:43:05,230 epoch 6 - iter 674/3375 - loss 0.12960435 - samples/sec: 594.96 - lr: 0.100000
121
+ 2022-08-06 17:43:09,879 epoch 6 - iter 1011/3375 - loss 0.13138410 - samples/sec: 582.36 - lr: 0.100000
122
+ 2022-08-06 17:43:14,516 epoch 6 - iter 1348/3375 - loss 0.13677806 - samples/sec: 583.86 - lr: 0.100000
123
+ 2022-08-06 17:43:18,882 epoch 6 - iter 1685/3375 - loss 0.13670652 - samples/sec: 620.11 - lr: 0.100000
124
+ 2022-08-06 17:43:23,704 epoch 6 - iter 2022/3375 - loss 0.13668428 - samples/sec: 561.38 - lr: 0.100000
125
+ 2022-08-06 17:43:28,769 epoch 6 - iter 2359/3375 - loss 0.13640742 - samples/sec: 534.52 - lr: 0.100000
126
+ 2022-08-06 17:43:33,236 epoch 6 - iter 2696/3375 - loss 0.13755392 - samples/sec: 606.04 - lr: 0.100000
127
+ 2022-08-06 17:43:37,586 epoch 6 - iter 3033/3375 - loss 0.13746161 - samples/sec: 622.08 - lr: 0.100000
128
+ 2022-08-06 17:43:42,082 epoch 6 - iter 3370/3375 - loss 0.13723492 - samples/sec: 602.17 - lr: 0.100000
129
+ 2022-08-06 17:43:42,147 ----------------------------------------------------------------------------------------------------
130
+ 2022-08-06 17:43:42,147 EPOCH 6 done: loss 0.1372 - lr 0.1000000
131
+ 2022-08-06 17:43:42,147 BAD EPOCHS (no improvement): 0
132
+ 2022-08-06 17:43:42,147 ----------------------------------------------------------------------------------------------------
133
+ 2022-08-06 17:43:46,395 epoch 7 - iter 337/3375 - loss 0.12821719 - samples/sec: 637.32 - lr: 0.100000
134
+ 2022-08-06 17:43:50,792 epoch 7 - iter 674/3375 - loss 0.12611973 - samples/sec: 615.63 - lr: 0.100000
135
+ 2022-08-06 17:43:55,039 epoch 7 - iter 1011/3375 - loss 0.13539270 - samples/sec: 637.45 - lr: 0.100000
136
+ 2022-08-06 17:44:00,049 epoch 7 - iter 1348/3375 - loss 0.13449392 - samples/sec: 540.37 - lr: 0.100000
137
+ 2022-08-06 17:44:05,561 epoch 7 - iter 1685/3375 - loss 0.13480434 - samples/sec: 491.30 - lr: 0.100000
138
+ 2022-08-06 17:44:09,812 epoch 7 - iter 2022/3375 - loss 0.13393960 - samples/sec: 636.70 - lr: 0.100000
139
+ 2022-08-06 17:44:14,239 epoch 7 - iter 2359/3375 - loss 0.13271508 - samples/sec: 611.43 - lr: 0.100000
140
+ 2022-08-06 17:44:18,867 epoch 7 - iter 2696/3375 - loss 0.13228520 - samples/sec: 584.91 - lr: 0.100000
141
+ 2022-08-06 17:44:23,521 epoch 7 - iter 3033/3375 - loss 0.13150334 - samples/sec: 581.80 - lr: 0.100000
142
+ 2022-08-06 17:44:27,942 epoch 7 - iter 3370/3375 - loss 0.13119164 - samples/sec: 612.23 - lr: 0.100000
143
+ 2022-08-06 17:44:28,021 ----------------------------------------------------------------------------------------------------
144
+ 2022-08-06 17:44:28,021 EPOCH 7 done: loss 0.1312 - lr 0.1000000
145
+ 2022-08-06 17:44:28,021 BAD EPOCHS (no improvement): 0
146
+ 2022-08-06 17:44:28,021 ----------------------------------------------------------------------------------------------------
147
+ 2022-08-06 17:44:32,652 epoch 8 - iter 337/3375 - loss 0.12551768 - samples/sec: 584.91 - lr: 0.100000
148
+ 2022-08-06 17:44:37,159 epoch 8 - iter 674/3375 - loss 0.12325345 - samples/sec: 600.67 - lr: 0.100000
149
+ 2022-08-06 17:44:41,564 epoch 8 - iter 1011/3375 - loss 0.12185993 - samples/sec: 614.59 - lr: 0.100000
150
+ 2022-08-06 17:44:46,122 epoch 8 - iter 1348/3375 - loss 0.12479223 - samples/sec: 593.84 - lr: 0.100000
151
+ 2022-08-06 17:44:50,413 epoch 8 - iter 1685/3375 - loss 0.12366948 - samples/sec: 630.75 - lr: 0.100000
152
+ 2022-08-06 17:44:54,842 epoch 8 - iter 2022/3375 - loss 0.12476122 - samples/sec: 611.10 - lr: 0.100000
153
+ 2022-08-06 17:45:00,389 epoch 8 - iter 2359/3375 - loss 0.12405554 - samples/sec: 488.28 - lr: 0.100000
154
+ 2022-08-06 17:45:04,761 epoch 8 - iter 2696/3375 - loss 0.12467999 - samples/sec: 619.20 - lr: 0.100000
155
+ 2022-08-06 17:45:09,105 epoch 8 - iter 3033/3375 - loss 0.12431931 - samples/sec: 623.01 - lr: 0.100000
156
+ 2022-08-06 17:45:13,364 epoch 8 - iter 3370/3375 - loss 0.12402088 - samples/sec: 635.69 - lr: 0.100000
157
+ 2022-08-06 17:45:13,423 ----------------------------------------------------------------------------------------------------
158
+ 2022-08-06 17:45:13,423 EPOCH 8 done: loss 0.1240 - lr 0.1000000
159
+ 2022-08-06 17:45:13,423 BAD EPOCHS (no improvement): 0
160
+ 2022-08-06 17:45:13,423 ----------------------------------------------------------------------------------------------------
161
+ 2022-08-06 17:45:17,588 epoch 9 - iter 337/3375 - loss 0.11869226 - samples/sec: 650.16 - lr: 0.100000
162
+ 2022-08-06 17:45:21,974 epoch 9 - iter 674/3375 - loss 0.11761429 - samples/sec: 617.37 - lr: 0.100000
163
+ 2022-08-06 17:45:26,393 epoch 9 - iter 1011/3375 - loss 0.12112653 - samples/sec: 612.52 - lr: 0.100000
164
+ 2022-08-06 17:45:30,523 epoch 9 - iter 1348/3375 - loss 0.12016456 - samples/sec: 655.50 - lr: 0.100000
165
+ 2022-08-06 17:45:34,854 epoch 9 - iter 1685/3375 - loss 0.11995454 - samples/sec: 624.96 - lr: 0.100000
166
+ 2022-08-06 17:45:39,585 epoch 9 - iter 2022/3375 - loss 0.12040979 - samples/sec: 572.27 - lr: 0.100000
167
+ 2022-08-06 17:45:44,002 epoch 9 - iter 2359/3375 - loss 0.12200073 - samples/sec: 612.84 - lr: 0.100000
168
+ 2022-08-06 17:45:48,278 epoch 9 - iter 2696/3375 - loss 0.12147852 - samples/sec: 633.10 - lr: 0.100000
169
+ 2022-08-06 17:45:52,885 epoch 9 - iter 3033/3375 - loss 0.12154468 - samples/sec: 587.68 - lr: 0.100000
170
+ 2022-08-06 17:45:57,272 epoch 9 - iter 3370/3375 - loss 0.12092220 - samples/sec: 616.99 - lr: 0.100000
171
+ 2022-08-06 17:45:57,355 ----------------------------------------------------------------------------------------------------
172
+ 2022-08-06 17:45:57,355 EPOCH 9 done: loss 0.1209 - lr 0.1000000
173
+ 2022-08-06 17:45:57,355 BAD EPOCHS (no improvement): 0
174
+ 2022-08-06 17:45:57,355 ----------------------------------------------------------------------------------------------------
175
+ 2022-08-06 17:46:01,777 epoch 10 - iter 337/3375 - loss 0.11757499 - samples/sec: 612.55 - lr: 0.100000
176
+ 2022-08-06 17:46:06,074 epoch 10 - iter 674/3375 - loss 0.11733099 - samples/sec: 629.81 - lr: 0.100000
177
+ 2022-08-06 17:46:10,355 epoch 10 - iter 1011/3375 - loss 0.11998283 - samples/sec: 632.25 - lr: 0.100000
178
+ 2022-08-06 17:46:14,824 epoch 10 - iter 1348/3375 - loss 0.11840153 - samples/sec: 605.68 - lr: 0.100000
179
+ 2022-08-06 17:46:19,148 epoch 10 - iter 1685/3375 - loss 0.11751962 - samples/sec: 626.11 - lr: 0.100000
180
+ 2022-08-06 17:46:23,634 epoch 10 - iter 2022/3375 - loss 0.11761529 - samples/sec: 603.43 - lr: 0.100000
181
+ 2022-08-06 17:46:28,564 epoch 10 - iter 2359/3375 - loss 0.11644619 - samples/sec: 549.14 - lr: 0.100000
182
+ 2022-08-06 17:46:33,013 epoch 10 - iter 2696/3375 - loss 0.11591934 - samples/sec: 608.57 - lr: 0.100000
183
+ 2022-08-06 17:46:37,268 epoch 10 - iter 3033/3375 - loss 0.11548489 - samples/sec: 636.19 - lr: 0.100000
184
+ 2022-08-06 17:46:41,953 epoch 10 - iter 3370/3375 - loss 0.11560614 - samples/sec: 577.69 - lr: 0.100000
185
+ 2022-08-06 17:46:42,039 ----------------------------------------------------------------------------------------------------
186
+ 2022-08-06 17:46:42,039 EPOCH 10 done: loss 0.1155 - lr 0.1000000
187
+ 2022-08-06 17:46:42,039 BAD EPOCHS (no improvement): 0
188
+ 2022-08-06 17:46:42,040 ----------------------------------------------------------------------------------------------------
189
+ 2022-08-06 17:46:47,051 epoch 11 - iter 337/3375 - loss 0.11148632 - samples/sec: 540.53 - lr: 0.100000
190
+ 2022-08-06 17:46:52,152 epoch 11 - iter 674/3375 - loss 0.11042773 - samples/sec: 530.65 - lr: 0.100000
191
+ 2022-08-06 17:46:57,169 epoch 11 - iter 1011/3375 - loss 0.10996054 - samples/sec: 539.75 - lr: 0.100000
192
+ 2022-08-06 17:47:02,418 epoch 11 - iter 1348/3375 - loss 0.11001571 - samples/sec: 515.88 - lr: 0.100000
193
+ 2022-08-06 17:47:06,655 epoch 11 - iter 1685/3375 - loss 0.11159141 - samples/sec: 639.03 - lr: 0.100000
194
+ 2022-08-06 17:47:10,921 epoch 11 - iter 2022/3375 - loss 0.11114012 - samples/sec: 634.58 - lr: 0.100000
195
+ 2022-08-06 17:47:15,457 epoch 11 - iter 2359/3375 - loss 0.11140276 - samples/sec: 596.99 - lr: 0.100000
196
+ 2022-08-06 17:47:19,724 epoch 11 - iter 2696/3375 - loss 0.11244845 - samples/sec: 634.31 - lr: 0.100000
197
+ 2022-08-06 17:47:24,060 epoch 11 - iter 3033/3375 - loss 0.11199352 - samples/sec: 624.32 - lr: 0.100000
198
+ 2022-08-06 17:47:28,621 epoch 11 - iter 3370/3375 - loss 0.11235823 - samples/sec: 593.47 - lr: 0.100000
199
+ 2022-08-06 17:47:28,710 ----------------------------------------------------------------------------------------------------
200
+ 2022-08-06 17:47:28,710 EPOCH 11 done: loss 0.1124 - lr 0.1000000
201
+ 2022-08-06 17:47:28,710 BAD EPOCHS (no improvement): 0
202
+ 2022-08-06 17:47:28,711 ----------------------------------------------------------------------------------------------------
203
+ 2022-08-06 17:47:33,603 epoch 12 - iter 337/3375 - loss 0.10261499 - samples/sec: 553.64 - lr: 0.100000
204
+ 2022-08-06 17:47:38,030 epoch 12 - iter 674/3375 - loss 0.10679532 - samples/sec: 611.69 - lr: 0.100000
205
+ 2022-08-06 17:47:42,435 epoch 12 - iter 1011/3375 - loss 0.10562828 - samples/sec: 614.62 - lr: 0.100000
206
+ 2022-08-06 17:47:46,797 epoch 12 - iter 1348/3375 - loss 0.10608638 - samples/sec: 620.71 - lr: 0.100000
207
+ 2022-08-06 17:47:51,540 epoch 12 - iter 1685/3375 - loss 0.10695263 - samples/sec: 570.80 - lr: 0.100000
208
+ 2022-08-06 17:47:56,079 epoch 12 - iter 2022/3375 - loss 0.10777783 - samples/sec: 596.42 - lr: 0.100000
209
+ 2022-08-06 17:48:00,835 epoch 12 - iter 2359/3375 - loss 0.10792335 - samples/sec: 569.39 - lr: 0.100000
210
+ 2022-08-06 17:48:05,686 epoch 12 - iter 2696/3375 - loss 0.10831173 - samples/sec: 558.08 - lr: 0.100000
211
+ 2022-08-06 17:48:10,274 epoch 12 - iter 3033/3375 - loss 0.10918512 - samples/sec: 590.06 - lr: 0.100000
212
+ 2022-08-06 17:48:14,536 epoch 12 - iter 3370/3375 - loss 0.10901718 - samples/sec: 635.12 - lr: 0.100000
213
+ 2022-08-06 17:48:14,587 ----------------------------------------------------------------------------------------------------
214
+ 2022-08-06 17:48:14,587 EPOCH 12 done: loss 0.1090 - lr 0.1000000
215
+ 2022-08-06 17:48:14,587 BAD EPOCHS (no improvement): 0
216
+ 2022-08-06 17:48:14,587 ----------------------------------------------------------------------------------------------------
217
+ 2022-08-06 17:48:18,825 epoch 13 - iter 337/3375 - loss 0.10530914 - samples/sec: 638.90 - lr: 0.100000
218
+ 2022-08-06 17:48:23,307 epoch 13 - iter 674/3375 - loss 0.10464441 - samples/sec: 603.86 - lr: 0.100000
219
+ 2022-08-06 17:48:27,651 epoch 13 - iter 1011/3375 - loss 0.10306362 - samples/sec: 623.29 - lr: 0.100000
220
+ 2022-08-06 17:48:32,134 epoch 13 - iter 1348/3375 - loss 0.10420551 - samples/sec: 603.86 - lr: 0.100000
221
+ 2022-08-06 17:48:36,266 epoch 13 - iter 1685/3375 - loss 0.10452131 - samples/sec: 655.29 - lr: 0.100000
222
+ 2022-08-06 17:48:40,833 epoch 13 - iter 2022/3375 - loss 0.10408465 - samples/sec: 592.81 - lr: 0.100000
223
+ 2022-08-06 17:48:45,313 epoch 13 - iter 2359/3375 - loss 0.10568763 - samples/sec: 604.26 - lr: 0.100000
224
+ 2022-08-06 17:48:49,615 epoch 13 - iter 2696/3375 - loss 0.10543009 - samples/sec: 629.36 - lr: 0.100000
225
+ 2022-08-06 17:48:54,244 epoch 13 - iter 3033/3375 - loss 0.10589822 - samples/sec: 584.89 - lr: 0.100000
226
+ 2022-08-06 17:48:58,821 epoch 13 - iter 3370/3375 - loss 0.10586039 - samples/sec: 591.43 - lr: 0.100000
227
+ 2022-08-06 17:48:58,876 ----------------------------------------------------------------------------------------------------
228
+ 2022-08-06 17:48:58,876 EPOCH 13 done: loss 0.1058 - lr 0.1000000
229
+ 2022-08-06 17:48:58,876 BAD EPOCHS (no improvement): 0
230
+ 2022-08-06 17:48:58,876 ----------------------------------------------------------------------------------------------------
231
+ 2022-08-06 17:49:03,753 epoch 14 - iter 337/3375 - loss 0.10266463 - samples/sec: 555.22 - lr: 0.100000
232
+ 2022-08-06 17:49:08,105 epoch 14 - iter 674/3375 - loss 0.09986994 - samples/sec: 622.09 - lr: 0.100000
233
+ 2022-08-06 17:49:12,382 epoch 14 - iter 1011/3375 - loss 0.10064186 - samples/sec: 632.97 - lr: 0.100000
234
+ 2022-08-06 17:49:16,500 epoch 14 - iter 1348/3375 - loss 0.10036665 - samples/sec: 657.29 - lr: 0.100000
235
+ 2022-08-06 17:49:20,879 epoch 14 - iter 1685/3375 - loss 0.10064704 - samples/sec: 618.21 - lr: 0.100000
236
+ 2022-08-06 17:49:25,715 epoch 14 - iter 2022/3375 - loss 0.10124885 - samples/sec: 559.90 - lr: 0.100000
237
+ 2022-08-06 17:49:30,441 epoch 14 - iter 2359/3375 - loss 0.10219313 - samples/sec: 572.62 - lr: 0.100000
238
+ 2022-08-06 17:49:35,333 epoch 14 - iter 2696/3375 - loss 0.10255165 - samples/sec: 553.46 - lr: 0.100000
239
+ 2022-08-06 17:49:40,241 epoch 14 - iter 3033/3375 - loss 0.10345096 - samples/sec: 551.63 - lr: 0.100000
240
+ 2022-08-06 17:49:44,508 epoch 14 - iter 3370/3375 - loss 0.10320104 - samples/sec: 634.41 - lr: 0.100000
241
+ 2022-08-06 17:49:44,571 ----------------------------------------------------------------------------------------------------
242
+ 2022-08-06 17:49:44,571 EPOCH 14 done: loss 0.1032 - lr 0.1000000
243
+ 2022-08-06 17:49:44,571 BAD EPOCHS (no improvement): 0
244
+ 2022-08-06 17:49:44,572 ----------------------------------------------------------------------------------------------------
245
+ 2022-08-06 17:49:48,789 epoch 15 - iter 337/3375 - loss 0.09291307 - samples/sec: 641.93 - lr: 0.100000
246
+ 2022-08-06 17:49:53,220 epoch 15 - iter 674/3375 - loss 0.09850943 - samples/sec: 611.07 - lr: 0.100000
247
+ 2022-08-06 17:49:58,173 epoch 15 - iter 1011/3375 - loss 0.09952572 - samples/sec: 546.65 - lr: 0.100000
248
+ 2022-08-06 17:50:02,751 epoch 15 - iter 1348/3375 - loss 0.10078682 - samples/sec: 591.25 - lr: 0.100000
249
+ 2022-08-06 17:50:07,256 epoch 15 - iter 1685/3375 - loss 0.09969399 - samples/sec: 601.10 - lr: 0.100000
250
+ 2022-08-06 17:50:11,608 epoch 15 - iter 2022/3375 - loss 0.09989152 - samples/sec: 621.99 - lr: 0.100000
251
+ 2022-08-06 17:50:16,244 epoch 15 - iter 2359/3375 - loss 0.09949392 - samples/sec: 583.90 - lr: 0.100000
252
+ 2022-08-06 17:50:20,702 epoch 15 - iter 2696/3375 - loss 0.09970785 - samples/sec: 607.41 - lr: 0.100000
253
+ 2022-08-06 17:50:25,046 epoch 15 - iter 3033/3375 - loss 0.09973762 - samples/sec: 623.09 - lr: 0.100000
254
+ 2022-08-06 17:50:30,228 epoch 15 - iter 3370/3375 - loss 0.10015630 - samples/sec: 522.57 - lr: 0.100000
255
+ 2022-08-06 17:50:30,326 ----------------------------------------------------------------------------------------------------
256
+ 2022-08-06 17:50:30,326 EPOCH 15 done: loss 0.1002 - lr 0.1000000
257
+ 2022-08-06 17:50:30,326 BAD EPOCHS (no improvement): 0
258
+ 2022-08-06 17:50:30,326 ----------------------------------------------------------------------------------------------------
259
+ 2022-08-06 17:50:34,860 epoch 16 - iter 337/3375 - loss 0.09309189 - samples/sec: 597.50 - lr: 0.100000
260
+ 2022-08-06 17:50:39,588 epoch 16 - iter 674/3375 - loss 0.09433545 - samples/sec: 572.69 - lr: 0.100000
261
+ 2022-08-06 17:50:43,862 epoch 16 - iter 1011/3375 - loss 0.09591019 - samples/sec: 633.44 - lr: 0.100000
262
+ 2022-08-06 17:50:48,264 epoch 16 - iter 1348/3375 - loss 0.09714011 - samples/sec: 615.21 - lr: 0.100000
263
+ 2022-08-06 17:50:52,778 epoch 16 - iter 1685/3375 - loss 0.09734419 - samples/sec: 599.67 - lr: 0.100000
264
+ 2022-08-06 17:50:56,980 epoch 16 - iter 2022/3375 - loss 0.09740550 - samples/sec: 644.23 - lr: 0.100000
265
+ 2022-08-06 17:51:01,265 epoch 16 - iter 2359/3375 - loss 0.09825085 - samples/sec: 631.79 - lr: 0.100000
266
+ 2022-08-06 17:51:05,586 epoch 16 - iter 2696/3375 - loss 0.09761991 - samples/sec: 626.34 - lr: 0.100000
267
+ 2022-08-06 17:51:09,789 epoch 16 - iter 3033/3375 - loss 0.09769947 - samples/sec: 644.03 - lr: 0.100000
268
+ 2022-08-06 17:51:14,125 epoch 16 - iter 3370/3375 - loss 0.09815652 - samples/sec: 624.14 - lr: 0.100000
269
+ 2022-08-06 17:51:14,187 ----------------------------------------------------------------------------------------------------
270
+ 2022-08-06 17:51:14,187 EPOCH 16 done: loss 0.0982 - lr 0.1000000
271
+ 2022-08-06 17:51:14,187 BAD EPOCHS (no improvement): 0
272
+ 2022-08-06 17:51:14,187 ----------------------------------------------------------------------------------------------------
273
+ 2022-08-06 17:51:18,926 epoch 17 - iter 337/3375 - loss 0.09746284 - samples/sec: 571.40 - lr: 0.100000
274
+ 2022-08-06 17:51:23,350 epoch 17 - iter 674/3375 - loss 0.09501375 - samples/sec: 611.81 - lr: 0.100000
275
+ 2022-08-06 17:51:27,538 epoch 17 - iter 1011/3375 - loss 0.09447877 - samples/sec: 646.43 - lr: 0.100000
276
+ 2022-08-06 17:51:32,786 epoch 17 - iter 1348/3375 - loss 0.09548126 - samples/sec: 515.91 - lr: 0.100000
277
+ 2022-08-06 17:51:37,524 epoch 17 - iter 1685/3375 - loss 0.09583694 - samples/sec: 571.43 - lr: 0.100000
278
+ 2022-08-06 17:51:42,195 epoch 17 - iter 2022/3375 - loss 0.09600862 - samples/sec: 579.61 - lr: 0.100000
279
+ 2022-08-06 17:51:46,571 epoch 17 - iter 2359/3375 - loss 0.09545410 - samples/sec: 618.73 - lr: 0.100000
280
+ 2022-08-06 17:51:51,161 epoch 17 - iter 2696/3375 - loss 0.09542768 - samples/sec: 589.75 - lr: 0.100000
281
+ 2022-08-06 17:51:55,581 epoch 17 - iter 3033/3375 - loss 0.09564076 - samples/sec: 612.22 - lr: 0.100000
282
+ 2022-08-06 17:52:00,366 epoch 17 - iter 3370/3375 - loss 0.09552351 - samples/sec: 565.88 - lr: 0.100000
283
+ 2022-08-06 17:52:00,466 ----------------------------------------------------------------------------------------------------
284
+ 2022-08-06 17:52:00,466 EPOCH 17 done: loss 0.0955 - lr 0.1000000
285
+ 2022-08-06 17:52:00,466 BAD EPOCHS (no improvement): 0
286
+ 2022-08-06 17:52:00,467 ----------------------------------------------------------------------------------------------------
287
+ 2022-08-06 17:52:05,126 epoch 18 - iter 337/3375 - loss 0.09523719 - samples/sec: 581.51 - lr: 0.100000
288
+ 2022-08-06 17:52:09,813 epoch 18 - iter 674/3375 - loss 0.09450967 - samples/sec: 577.48 - lr: 0.100000
289
+ 2022-08-06 17:52:14,214 epoch 18 - iter 1011/3375 - loss 0.09350620 - samples/sec: 614.93 - lr: 0.100000
290
+ 2022-08-06 17:52:18,695 epoch 18 - iter 1348/3375 - loss 0.09537413 - samples/sec: 604.13 - lr: 0.100000
291
+ 2022-08-06 17:52:23,194 epoch 18 - iter 1685/3375 - loss 0.09425488 - samples/sec: 601.78 - lr: 0.100000
292
+ 2022-08-06 17:52:27,455 epoch 18 - iter 2022/3375 - loss 0.09334668 - samples/sec: 635.22 - lr: 0.100000
293
+ 2022-08-06 17:52:31,848 epoch 18 - iter 2359/3375 - loss 0.09344352 - samples/sec: 616.12 - lr: 0.100000
294
+ 2022-08-06 17:52:36,473 epoch 18 - iter 2696/3375 - loss 0.09299327 - samples/sec: 585.57 - lr: 0.100000
295
+ 2022-08-06 17:52:41,003 epoch 18 - iter 3033/3375 - loss 0.09300260 - samples/sec: 597.47 - lr: 0.100000
296
+ 2022-08-06 17:52:45,386 epoch 18 - iter 3370/3375 - loss 0.09343840 - samples/sec: 617.52 - lr: 0.100000
297
+ 2022-08-06 17:52:45,447 ----------------------------------------------------------------------------------------------------
298
+ 2022-08-06 17:52:45,447 EPOCH 18 done: loss 0.0934 - lr 0.1000000
299
+ 2022-08-06 17:52:45,447 BAD EPOCHS (no improvement): 0
300
+ 2022-08-06 17:52:45,447 ----------------------------------------------------------------------------------------------------
301
+ 2022-08-06 17:52:50,328 epoch 19 - iter 337/3375 - loss 0.09183730 - samples/sec: 555.07 - lr: 0.100000
302
+ 2022-08-06 17:52:54,916 epoch 19 - iter 674/3375 - loss 0.09369803 - samples/sec: 590.07 - lr: 0.100000
303
+ 2022-08-06 17:52:59,194 epoch 19 - iter 1011/3375 - loss 0.09249498 - samples/sec: 632.78 - lr: 0.100000
304
+ 2022-08-06 17:53:04,075 epoch 19 - iter 1348/3375 - loss 0.09142685 - samples/sec: 554.67 - lr: 0.100000
305
+ 2022-08-06 17:53:08,444 epoch 19 - iter 1685/3375 - loss 0.09456761 - samples/sec: 619.54 - lr: 0.100000
306
+ 2022-08-06 17:53:12,935 epoch 19 - iter 2022/3375 - loss 0.09320509 - samples/sec: 602.65 - lr: 0.100000
307
+ 2022-08-06 17:53:17,403 epoch 19 - iter 2359/3375 - loss 0.09305377 - samples/sec: 605.93 - lr: 0.100000
308
+ 2022-08-06 17:53:21,539 epoch 19 - iter 2696/3375 - loss 0.09314087 - samples/sec: 654.49 - lr: 0.100000
309
+ 2022-08-06 17:53:25,681 epoch 19 - iter 3033/3375 - loss 0.09290888 - samples/sec: 653.59 - lr: 0.100000
310
+ 2022-08-06 17:53:30,867 epoch 19 - iter 3370/3375 - loss 0.09356361 - samples/sec: 522.02 - lr: 0.100000
311
+ 2022-08-06 17:53:30,949 ----------------------------------------------------------------------------------------------------
312
+ 2022-08-06 17:53:30,950 EPOCH 19 done: loss 0.0936 - lr 0.1000000
313
+ 2022-08-06 17:53:30,950 BAD EPOCHS (no improvement): 1
314
+ 2022-08-06 17:53:30,950 ----------------------------------------------------------------------------------------------------
315
+ 2022-08-06 17:53:35,766 epoch 20 - iter 337/3375 - loss 0.08592285 - samples/sec: 562.61 - lr: 0.100000
316
+ 2022-08-06 17:53:40,368 epoch 20 - iter 674/3375 - loss 0.08824294 - samples/sec: 588.15 - lr: 0.100000
317
+ 2022-08-06 17:53:44,867 epoch 20 - iter 1011/3375 - loss 0.08782340 - samples/sec: 601.81 - lr: 0.100000
318
+ 2022-08-06 17:53:49,378 epoch 20 - iter 1348/3375 - loss 0.08879308 - samples/sec: 600.08 - lr: 0.100000
319
+ 2022-08-06 17:53:53,750 epoch 20 - iter 1685/3375 - loss 0.08912537 - samples/sec: 619.31 - lr: 0.100000
320
+ 2022-08-06 17:53:58,438 epoch 20 - iter 2022/3375 - loss 0.08964443 - samples/sec: 577.38 - lr: 0.100000
321
+ 2022-08-06 17:54:03,640 epoch 20 - iter 2359/3375 - loss 0.09111402 - samples/sec: 520.50 - lr: 0.100000
322
+ 2022-08-06 17:54:08,314 epoch 20 - iter 2696/3375 - loss 0.09094169 - samples/sec: 579.27 - lr: 0.100000
323
+ 2022-08-06 17:54:12,604 epoch 20 - iter 3033/3375 - loss 0.09075914 - samples/sec: 631.05 - lr: 0.100000
324
+ 2022-08-06 17:54:16,884 epoch 20 - iter 3370/3375 - loss 0.09071504 - samples/sec: 632.42 - lr: 0.100000
325
+ 2022-08-06 17:54:16,961 ----------------------------------------------------------------------------------------------------
326
+ 2022-08-06 17:54:16,961 EPOCH 20 done: loss 0.0907 - lr 0.1000000
327
+ 2022-08-06 17:54:16,961 BAD EPOCHS (no improvement): 0
328
+ 2022-08-06 17:54:16,962 ----------------------------------------------------------------------------------------------------
329
+ 2022-08-06 17:54:21,579 epoch 21 - iter 337/3375 - loss 0.08841872 - samples/sec: 586.44 - lr: 0.100000
330
+ 2022-08-06 17:54:25,873 epoch 21 - iter 674/3375 - loss 0.09033463 - samples/sec: 630.54 - lr: 0.100000
331
+ 2022-08-06 17:54:30,408 epoch 21 - iter 1011/3375 - loss 0.08778770 - samples/sec: 596.92 - lr: 0.100000
332
+ 2022-08-06 17:54:35,094 epoch 21 - iter 1348/3375 - loss 0.08826479 - samples/sec: 577.63 - lr: 0.100000
333
+ 2022-08-06 17:54:39,794 epoch 21 - iter 1685/3375 - loss 0.08952893 - samples/sec: 575.93 - lr: 0.100000
334
+ 2022-08-06 17:54:44,231 epoch 21 - iter 2022/3375 - loss 0.08859231 - samples/sec: 610.18 - lr: 0.100000
335
+ 2022-08-06 17:54:48,578 epoch 21 - iter 2359/3375 - loss 0.08908605 - samples/sec: 622.78 - lr: 0.100000
336
+ 2022-08-06 17:54:53,007 epoch 21 - iter 2696/3375 - loss 0.08985834 - samples/sec: 611.21 - lr: 0.100000
337
+ 2022-08-06 17:54:57,442 epoch 21 - iter 3033/3375 - loss 0.08930750 - samples/sec: 610.45 - lr: 0.100000
338
+ 2022-08-06 17:55:02,206 epoch 21 - iter 3370/3375 - loss 0.08932127 - samples/sec: 568.31 - lr: 0.100000
339
+ 2022-08-06 17:55:02,283 ----------------------------------------------------------------------------------------------------
340
+ 2022-08-06 17:55:02,283 EPOCH 21 done: loss 0.0894 - lr 0.1000000
341
+ 2022-08-06 17:55:02,283 BAD EPOCHS (no improvement): 0
342
+ 2022-08-06 17:55:02,283 ----------------------------------------------------------------------------------------------------
343
+ 2022-08-06 17:55:06,802 epoch 22 - iter 337/3375 - loss 0.09520887 - samples/sec: 599.23 - lr: 0.100000
344
+ 2022-08-06 17:55:10,986 epoch 22 - iter 674/3375 - loss 0.08822703 - samples/sec: 646.83 - lr: 0.100000
345
+ 2022-08-06 17:55:15,255 epoch 22 - iter 1011/3375 - loss 0.08622536 - samples/sec: 634.09 - lr: 0.100000
346
+ 2022-08-06 17:55:19,649 epoch 22 - iter 1348/3375 - loss 0.08564414 - samples/sec: 616.17 - lr: 0.100000
347
+ 2022-08-06 17:55:24,104 epoch 22 - iter 1685/3375 - loss 0.08673066 - samples/sec: 607.75 - lr: 0.100000
348
+ 2022-08-06 17:55:28,976 epoch 22 - iter 2022/3375 - loss 0.08631774 - samples/sec: 555.74 - lr: 0.100000
349
+ 2022-08-06 17:55:34,330 epoch 22 - iter 2359/3375 - loss 0.08715661 - samples/sec: 505.64 - lr: 0.100000
350
+ 2022-08-06 17:55:38,933 epoch 22 - iter 2696/3375 - loss 0.08728198 - samples/sec: 588.32 - lr: 0.100000
351
+ 2022-08-06 17:55:43,208 epoch 22 - iter 3033/3375 - loss 0.08684389 - samples/sec: 633.19 - lr: 0.100000
352
+ 2022-08-06 17:55:47,534 epoch 22 - iter 3370/3375 - loss 0.08722766 - samples/sec: 625.79 - lr: 0.100000
353
+ 2022-08-06 17:55:47,604 ----------------------------------------------------------------------------------------------------
354
+ 2022-08-06 17:55:47,604 EPOCH 22 done: loss 0.0872 - lr 0.1000000
355
+ 2022-08-06 17:55:47,604 BAD EPOCHS (no improvement): 0
356
+ 2022-08-06 17:55:47,604 ----------------------------------------------------------------------------------------------------
357
+ 2022-08-06 17:55:52,186 epoch 23 - iter 337/3375 - loss 0.08017333 - samples/sec: 590.96 - lr: 0.100000
358
+ 2022-08-06 17:55:56,925 epoch 23 - iter 674/3375 - loss 0.08566375 - samples/sec: 571.20 - lr: 0.100000
359
+ 2022-08-06 17:56:02,124 epoch 23 - iter 1011/3375 - loss 0.08434552 - samples/sec: 520.85 - lr: 0.100000
360
+ 2022-08-06 17:56:06,416 epoch 23 - iter 1348/3375 - loss 0.08355178 - samples/sec: 630.72 - lr: 0.100000
361
+ 2022-08-06 17:56:10,582 epoch 23 - iter 1685/3375 - loss 0.08448399 - samples/sec: 649.88 - lr: 0.100000
362
+ 2022-08-06 17:56:14,769 epoch 23 - iter 2022/3375 - loss 0.08326237 - samples/sec: 646.48 - lr: 0.100000
363
+ 2022-08-06 17:56:20,143 epoch 23 - iter 2359/3375 - loss 0.08403657 - samples/sec: 503.87 - lr: 0.100000
364
+ 2022-08-06 17:56:24,669 epoch 23 - iter 2696/3375 - loss 0.08457048 - samples/sec: 598.22 - lr: 0.100000
365
+ 2022-08-06 17:56:29,782 epoch 23 - iter 3033/3375 - loss 0.08508802 - samples/sec: 529.51 - lr: 0.100000
366
+ 2022-08-06 17:56:35,014 epoch 23 - iter 3370/3375 - loss 0.08481329 - samples/sec: 517.53 - lr: 0.100000
367
+ 2022-08-06 17:56:35,074 ----------------------------------------------------------------------------------------------------
368
+ 2022-08-06 17:56:35,074 EPOCH 23 done: loss 0.0848 - lr 0.1000000
369
+ 2022-08-06 17:56:35,074 BAD EPOCHS (no improvement): 0
370
+ 2022-08-06 17:56:35,074 ----------------------------------------------------------------------------------------------------
371
+ 2022-08-06 17:56:39,343 epoch 24 - iter 337/3375 - loss 0.07795316 - samples/sec: 634.54 - lr: 0.100000
372
+ 2022-08-06 17:56:43,602 epoch 24 - iter 674/3375 - loss 0.08697526 - samples/sec: 635.47 - lr: 0.100000
373
+ 2022-08-06 17:56:47,867 epoch 24 - iter 1011/3375 - loss 0.08509757 - samples/sec: 634.63 - lr: 0.100000
374
+ 2022-08-06 17:56:52,131 epoch 24 - iter 1348/3375 - loss 0.08401546 - samples/sec: 634.87 - lr: 0.100000
375
+ 2022-08-06 17:56:56,703 epoch 24 - iter 1685/3375 - loss 0.08334637 - samples/sec: 592.23 - lr: 0.100000
376
+ 2022-08-06 17:57:01,803 epoch 24 - iter 2022/3375 - loss 0.08350469 - samples/sec: 530.86 - lr: 0.100000
377
+ 2022-08-06 17:57:06,426 epoch 24 - iter 2359/3375 - loss 0.08457126 - samples/sec: 585.70 - lr: 0.100000
378
+ 2022-08-06 17:57:10,620 epoch 24 - iter 2696/3375 - loss 0.08411288 - samples/sec: 645.43 - lr: 0.100000
379
+ 2022-08-06 17:57:15,195 epoch 24 - iter 3033/3375 - loss 0.08372175 - samples/sec: 591.91 - lr: 0.100000
380
+ 2022-08-06 17:57:19,534 epoch 24 - iter 3370/3375 - loss 0.08385091 - samples/sec: 623.89 - lr: 0.100000
381
+ 2022-08-06 17:57:19,597 ----------------------------------------------------------------------------------------------------
382
+ 2022-08-06 17:57:19,597 EPOCH 24 done: loss 0.0839 - lr 0.1000000
383
+ 2022-08-06 17:57:19,598 BAD EPOCHS (no improvement): 0
384
+ 2022-08-06 17:57:19,598 ----------------------------------------------------------------------------------------------------
385
+ 2022-08-06 17:57:24,012 epoch 25 - iter 337/3375 - loss 0.08110875 - samples/sec: 613.40 - lr: 0.100000
386
+ 2022-08-06 17:57:28,406 epoch 25 - iter 674/3375 - loss 0.07892701 - samples/sec: 615.98 - lr: 0.100000
387
+ 2022-08-06 17:57:33,858 epoch 25 - iter 1011/3375 - loss 0.07994063 - samples/sec: 496.56 - lr: 0.100000
388
+ 2022-08-06 17:57:38,355 epoch 25 - iter 1348/3375 - loss 0.08204104 - samples/sec: 601.98 - lr: 0.100000
389
+ 2022-08-06 17:57:42,644 epoch 25 - iter 1685/3375 - loss 0.08232195 - samples/sec: 631.36 - lr: 0.100000
390
+ 2022-08-06 17:57:47,142 epoch 25 - iter 2022/3375 - loss 0.08153107 - samples/sec: 601.89 - lr: 0.100000
391
+ 2022-08-06 17:57:51,622 epoch 25 - iter 2359/3375 - loss 0.08242419 - samples/sec: 604.33 - lr: 0.100000
392
+ 2022-08-06 17:57:56,375 epoch 25 - iter 2696/3375 - loss 0.08252423 - samples/sec: 569.51 - lr: 0.100000
393
+ 2022-08-06 17:58:01,711 epoch 25 - iter 3033/3375 - loss 0.08258040 - samples/sec: 507.42 - lr: 0.100000
394
+ 2022-08-06 17:58:06,572 epoch 25 - iter 3370/3375 - loss 0.08268759 - samples/sec: 557.05 - lr: 0.100000
395
+ 2022-08-06 17:58:06,635 ----------------------------------------------------------------------------------------------------
396
+ 2022-08-06 17:58:06,635 EPOCH 25 done: loss 0.0827 - lr 0.1000000
397
+ 2022-08-06 17:58:06,635 BAD EPOCHS (no improvement): 0
398
+ 2022-08-06 17:58:07,628 ----------------------------------------------------------------------------------------------------
399
+ 2022-08-06 17:58:07,629 Testing using last state of model ...
400
+ 2022-08-06 18:01:16,199 0.9702 0.9702 0.9702 0.9702
401
+ 2022-08-06 18:01:16,200
402
  Results:
403
+ - F-score (micro) 0.9702
404
+ - F-score (macro) 0.882
405
+ - Accuracy 0.9702
406
 
407
  By class:
408
  precision recall f1-score support
409
 
410
+ N_SING 0.9757 0.9621 0.9689 30553
411
+ P 0.9586 0.9948 0.9764 9951
412
+ DELM 0.9985 0.9996 0.9991 8122
413
+ ADJ 0.9154 0.9379 0.9265 7466
414
+ CON 0.9913 0.9811 0.9862 6823
415
+ N_PL 0.9803 0.9733 0.9768 5163
416
+ V_PA 0.9799 0.9822 0.9811 2873
417
+ V_PRS 0.9947 0.9894 0.9921 2841
418
+ NUM 0.9942 0.9978 0.9960 2232
419
+ PRO 0.9711 0.9522 0.9615 2258
420
+ DET 0.9576 0.9633 0.9605 1853
421
+ CLITIC 1.0000 1.0000 1.0000 1259
422
+ V_PP 0.9742 0.9767 0.9754 1158
423
+ V_SUB 0.9822 0.9661 0.9741 1031
424
+ ADV 0.8607 0.8705 0.8655 880
425
+ ADV_TIME 0.9183 0.9652 0.9412 489
426
+ V_AUX 0.9921 0.9947 0.9934 379
427
+ ADJ_SUP 0.9926 0.9889 0.9907 270
428
+ ADJ_CMPR 0.9397 0.9689 0.9541 193
429
+ ADJ_INO 0.8312 0.7619 0.7950 168
430
+ ADV_NEG 0.9357 0.8792 0.9066 149
431
+ ADV_I 0.8740 0.7929 0.8315 140
432
+ FW 0.6500 0.6341 0.6420 123
433
+ ADV_COMP 0.8043 0.9737 0.8810 76
434
+ ADV_LOC 0.9726 0.9726 0.9726 73
435
+ V_IMP 0.7091 0.6964 0.7027 56
436
+ PREV 0.7742 0.7500 0.7619 32
437
+ INT 0.7778 0.5833 0.6667 24
438
+ N_VOC 0.0000 0.0000 0.0000 0
439
 
440
+ micro avg 0.9702 0.9702 0.9702 86635
441
+ macro avg 0.8864 0.8796 0.8820 86635
442
+ weighted avg 0.9704 0.9702 0.9702 86635
443
+ samples avg 0.9702 0.9702 0.9702 86635
444
 
445
+ 2022-08-06 18:01:16,200 ----------------------------------------------------------------------------------------------------