-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathinfCheXbert_full_integration.txt
888 lines (888 loc) · 60.9 KB
/
infCheXbert_full_integration.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
lr= 1e-5
dropout rate: 0.1
Batch size: 16
training time: 7765 min (7725+40)
The number of training instances: 99371
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 100, Avg loss: 1.088
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 200, Avg loss: 0.741
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 300, Avg loss: 0.619
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 400, Avg loss: 0.493
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 500, Avg loss: 0.406
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 600, Avg loss: 0.359
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 700, Avg loss: 0.359
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 800, Avg loss: 0.332
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 900, Avg loss: 0.293
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 1000, Avg loss: 0.301
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 1100, Avg loss: 0.246
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 1200, Avg loss: 0.309
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 1300, Avg loss: 0.259
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 1400, Avg loss: 0.227
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 1500, Avg loss: 0.279
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 1600, Avg loss: 0.258
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 1700, Avg loss: 0.246
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 1800, Avg loss: 0.259
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 1900, Avg loss: 0.292
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 2000, Avg loss: 0.242
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 2100, Avg loss: 0.254
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 2200, Avg loss: 0.265
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 2300, Avg loss: 0.229
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 2400, Avg loss: 0.254
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 2500, Avg loss: 0.250
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 2600, Avg loss: 0.231
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 2700, Avg loss: 0.293
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 2800, Avg loss: 0.245
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 2900, Avg loss: 0.239
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 3000, Avg loss: 0.250
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 3100, Avg loss: 0.284
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 3200, Avg loss: 0.255
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 3300, Avg loss: 0.247
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 3400, Avg loss: 0.227
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 3500, Avg loss: 0.258
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 3600, Avg loss: 0.278
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 3700, Avg loss: 0.279
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 3800, Avg loss: 0.243
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 3900, Avg loss: 0.259
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 4000, Avg loss: 0.236
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 4100, Avg loss: 0.237
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 4200, Avg loss: 0.223
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 4300, Avg loss: 0.268
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 4400, Avg loss: 0.202
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 4500, Avg loss: 0.251
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 4600, Avg loss: 0.228
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 4700, Avg loss: 0.250
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 4800, Avg loss: 0.201
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 4900, Avg loss: 0.199
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 5000, Avg loss: 0.221
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 5100, Avg loss: 0.252
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 5200, Avg loss: 0.179
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 5300, Avg loss: 0.191
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 5400, Avg loss: 0.217
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 5500, Avg loss: 0.247
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 5600, Avg loss: 0.208
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 5700, Avg loss: 0.166
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 5800, Avg loss: 0.201
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 5900, Avg loss: 0.214
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 6000, Avg loss: 0.183
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 6100, Avg loss: 0.197
labelsname: label_Atelectasis, Epoch id: 1, Training steps: 6200, Avg loss: 0.167
Start evaluation on test dataset.
Loading sentences from ./datasets/CheXpert/impression/validation.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
labelsname: label_Atelectasis, Label_value 0: 0.982, 0.982, 0.982
labelsname: label_Atelectasis, Label_value 1: 0.813, 0.813, 0.813
model never predicts label value 2
labelsname: label_Atelectasis, Label_value 2: 0.000, 0.000, 0.000
labelsname: label_Atelectasis, Label_value 3: 0.812, 0.812, 0.812
Acc. (Correct/Total): 0.9418 (31195/33124)
Start evaluation on evaluation dataset.
Loading sentences from ./datasets/CheXpert/impression/test.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
The number of evaluation instances: 33124
Confusion matrix of {label_name}:
tensor([[24701, 341, 14, 85],
[ 11, 6096, 193, 1210],
[ 0, 0, 0, 0],
[ 1, 87, 3, 382]])
Report precision, recall, and f1:
labelsname: label_Atelectasis, Label_value 0: 0.982, 0.982, 0.982
labelsname: label_Atelectasis, Label_value 1: 0.812, 0.812, 0.812
model never predicts label value 2
labelsname: label_Atelectasis, Label_value 2: 0.000, 0.000, 0.000
labelsname: label_Atelectasis, Label_value 3: 0.808, 0.808, 0.808
Acc. (Correct/Total): 0.9413 (31179/33124)
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 100, Avg loss: 0.196
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 200, Avg loss: 0.172
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 300, Avg loss: 0.211
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 400, Avg loss: 0.207
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 500, Avg loss: 0.195
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 600, Avg loss: 0.178
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 700, Avg loss: 0.204
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 800, Avg loss: 0.166
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 900, Avg loss: 0.164
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 1000, Avg loss: 0.176
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 1100, Avg loss: 0.166
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 1200, Avg loss: 0.224
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 1300, Avg loss: 0.161
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 1400, Avg loss: 0.162
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 1500, Avg loss: 0.215
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 1600, Avg loss: 0.193
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 1700, Avg loss: 0.177
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 1800, Avg loss: 0.169
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 1900, Avg loss: 0.210
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 2000, Avg loss: 0.164
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 2100, Avg loss: 0.200
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 2200, Avg loss: 0.161
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 2300, Avg loss: 0.142
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 2400, Avg loss: 0.167
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 2500, Avg loss: 0.186
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 2600, Avg loss: 0.164
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 2700, Avg loss: 0.220
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 2800, Avg loss: 0.181
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 2900, Avg loss: 0.151
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 3000, Avg loss: 0.164
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 3100, Avg loss: 0.189
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 3200, Avg loss: 0.184
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 3300, Avg loss: 0.185
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 3400, Avg loss: 0.170
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 3500, Avg loss: 0.190
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 3600, Avg loss: 0.199
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 3700, Avg loss: 0.200
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 3800, Avg loss: 0.179
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 3900, Avg loss: 0.186
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 4000, Avg loss: 0.173
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 4100, Avg loss: 0.168
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 4200, Avg loss: 0.170
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 4300, Avg loss: 0.181
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 4400, Avg loss: 0.141
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 4500, Avg loss: 0.184
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 4600, Avg loss: 0.175
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 4700, Avg loss: 0.201
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 4800, Avg loss: 0.154
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 4900, Avg loss: 0.147
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 5000, Avg loss: 0.153
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 5100, Avg loss: 0.197
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 5200, Avg loss: 0.123
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 5300, Avg loss: 0.160
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 5400, Avg loss: 0.182
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 5500, Avg loss: 0.222
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 5600, Avg loss: 0.178
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 5700, Avg loss: 0.148
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 5800, Avg loss: 0.181
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 5900, Avg loss: 0.201
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 6000, Avg loss: 0.161
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 6100, Avg loss: 0.177
labelsname: label_Atelectasis, Epoch id: 2, Training steps: 6200, Avg loss: 0.151
Start evaluation on test dataset.
Loading sentences from ./datasets/CheXpert/impression/validation.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
labelsname: label_Atelectasis, Label_value 0: 0.984, 0.984, 0.984
labelsname: label_Atelectasis, Label_value 1: 0.832, 0.832, 0.832
model never predicts label value 2
labelsname: label_Atelectasis, Label_value 2: 0.000, 0.000, 0.000
labelsname: label_Atelectasis, Label_value 3: 0.795, 0.795, 0.795
Acc. (Correct/Total): 0.9467 (31360/33124)
Start evaluation on evaluation dataset.
Loading sentences from ./datasets/CheXpert/impression/test.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
The number of evaluation instances: 33124
Confusion matrix of {label_name}:
tensor([[24700, 315, 11, 79],
[ 12, 6076, 195, 1038],
[ 0, 0, 0, 0],
[ 1, 133, 4, 560]])
Report precision, recall, and f1:
labelsname: label_Atelectasis, Label_value 0: 0.984, 0.984, 0.984
labelsname: label_Atelectasis, Label_value 1: 0.830, 0.830, 0.830
model never predicts label value 2
labelsname: label_Atelectasis, Label_value 2: 0.000, 0.000, 0.000
labelsname: label_Atelectasis, Label_value 3: 0.802, 0.802, 0.802
Acc. (Correct/Total): 0.9460 (31336/33124)
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 100, Avg loss: 0.173
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 200, Avg loss: 0.150
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 300, Avg loss: 0.201
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 400, Avg loss: 0.191
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 500, Avg loss: 0.188
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 600, Avg loss: 0.158
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 700, Avg loss: 0.191
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 800, Avg loss: 0.160
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 900, Avg loss: 0.148
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 1000, Avg loss: 0.159
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 1100, Avg loss: 0.154
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 1200, Avg loss: 0.210
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 1300, Avg loss: 0.154
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 1400, Avg loss: 0.146
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 1500, Avg loss: 0.209
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 1600, Avg loss: 0.180
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 1700, Avg loss: 0.167
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 1800, Avg loss: 0.166
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 1900, Avg loss: 0.193
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 2000, Avg loss: 0.152
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 2100, Avg loss: 0.182
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 2200, Avg loss: 0.162
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 2300, Avg loss: 0.140
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 2400, Avg loss: 0.161
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 2500, Avg loss: 0.177
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 2600, Avg loss: 0.162
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 2700, Avg loss: 0.208
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 2800, Avg loss: 0.164
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 2900, Avg loss: 0.147
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 3000, Avg loss: 0.159
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 3100, Avg loss: 0.175
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 3200, Avg loss: 0.185
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 3300, Avg loss: 0.176
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 3400, Avg loss: 0.166
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 3500, Avg loss: 0.178
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 3600, Avg loss: 0.188
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 3700, Avg loss: 0.188
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 3800, Avg loss: 0.174
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 3900, Avg loss: 0.170
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 4000, Avg loss: 0.155
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 4100, Avg loss: 0.160
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 4200, Avg loss: 0.158
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 4300, Avg loss: 0.166
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 4400, Avg loss: 0.126
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 4500, Avg loss: 0.176
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 4600, Avg loss: 0.169
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 4700, Avg loss: 0.199
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 4800, Avg loss: 0.140
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 4900, Avg loss: 0.148
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 5000, Avg loss: 0.147
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 5100, Avg loss: 0.185
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 5200, Avg loss: 0.116
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 5300, Avg loss: 0.152
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 5400, Avg loss: 0.173
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 5500, Avg loss: 0.211
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 5600, Avg loss: 0.167
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 5700, Avg loss: 0.142
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 5800, Avg loss: 0.169
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 5900, Avg loss: 0.188
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 6000, Avg loss: 0.159
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 6100, Avg loss: 0.165
labelsname: label_Atelectasis, Epoch id: 3, Training steps: 6200, Avg loss: 0.148
Start evaluation on test dataset.
Loading sentences from ./datasets/CheXpert/impression/validation.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
labelsname: label_Atelectasis, Label_value 0: 0.984, 0.984, 0.984
labelsname: label_Atelectasis, Label_value 1: 0.827, 0.827, 0.827
model never predicts label value 2
labelsname: label_Atelectasis, Label_value 2: 0.000, 0.000, 0.000
labelsname: label_Atelectasis, Label_value 3: 0.805, 0.805, 0.805
Acc. (Correct/Total): 0.9459 (31332/33124)
Final evaluation on the evaluation dataset.
Loading sentences from ./datasets/CheXpert/impression/test.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
The number of evaluation instances: 33124
Confusion matrix of {label_name}:
tensor([[24700, 315, 11, 79],
[ 12, 6076, 195, 1038],
[ 0, 0, 0, 0],
[ 1, 133, 4, 560]])
Report precision, recall, and f1:
labelsname: label_Atelectasis, Label_value 0: 0.984, 0.984, 0.984
labelsname: label_Atelectasis, Label_value 1: 0.830, 0.830, 0.830
model never predicts label value 2
labelsname: label_Atelectasis, Label_value 2: 0.000, 0.000, 0.000
labelsname: label_Atelectasis, Label_value 3: 0.802, 0.802, 0.802
Acc. (Correct/Total): 0.9460 (31336/33124)
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 100, Avg loss: 1.073
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 200, Avg loss: 0.773
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 300, Avg loss: 0.693
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 400, Avg loss: 0.633
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 500, Avg loss: 0.637
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 600, Avg loss: 0.606
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 700, Avg loss: 0.583
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 800, Avg loss: 0.516
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 900, Avg loss: 0.507
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 1000, Avg loss: 0.476
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 1100, Avg loss: 0.442
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 1200, Avg loss: 0.398
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 1300, Avg loss: 0.396
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 1400, Avg loss: 0.372
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 1500, Avg loss: 0.405
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 1600, Avg loss: 0.374
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 1700, Avg loss: 0.362
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 1800, Avg loss: 0.368
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 1900, Avg loss: 0.384
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 2000, Avg loss: 0.288
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 2100, Avg loss: 0.342
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 2200, Avg loss: 0.383
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 2300, Avg loss: 0.315
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 2400, Avg loss: 0.318
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 2500, Avg loss: 0.347
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 2600, Avg loss: 0.285
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 2700, Avg loss: 0.268
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 2800, Avg loss: 0.290
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 2900, Avg loss: 0.267
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 3000, Avg loss: 0.285
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 3100, Avg loss: 0.290
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 3200, Avg loss: 0.277
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 3300, Avg loss: 0.298
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 3400, Avg loss: 0.277
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 3500, Avg loss: 0.264
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 3600, Avg loss: 0.251
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 3700, Avg loss: 0.240
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 3800, Avg loss: 0.235
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 3900, Avg loss: 0.217
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 4000, Avg loss: 0.276
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 4100, Avg loss: 0.252
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 4200, Avg loss: 0.222
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 4300, Avg loss: 0.238
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 4400, Avg loss: 0.231
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 4500, Avg loss: 0.224
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 4600, Avg loss: 0.237
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 4700, Avg loss: 0.220
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 4800, Avg loss: 0.249
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 4900, Avg loss: 0.217
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 5000, Avg loss: 0.199
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 5100, Avg loss: 0.263
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 5200, Avg loss: 0.201
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 5300, Avg loss: 0.201
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 5400, Avg loss: 0.209
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 5500, Avg loss: 0.195
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 5600, Avg loss: 0.222
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 5700, Avg loss: 0.201
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 5800, Avg loss: 0.242
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 5900, Avg loss: 0.208
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 6000, Avg loss: 0.215
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 6100, Avg loss: 0.238
labelsname: label_Cardiomegaly, Epoch id: 1, Training steps: 6200, Avg loss: 0.210
Start evaluation on test dataset.
Loading sentences from ./datasets/CheXpert/impression/validation.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
labelsname: label_Cardiomegaly, Label_value 0: 0.981, 0.981, 0.981
labelsname: label_Cardiomegaly, Label_value 1: 0.929, 0.929, 0.929
labelsname: label_Cardiomegaly, Label_value 2: 0.709, 0.709, 0.709
labelsname: label_Cardiomegaly, Label_value 3: 0.732, 0.732, 0.732
Acc. (Correct/Total): 0.9450 (31303/33124)
Start evaluation on evaluation dataset.
Loading sentences from ./datasets/CheXpert/impression/test.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
The number of evaluation instances: 33124
Confusion matrix of {label_name}:
tensor([[23735, 249, 48, 171],
[ 165, 5201, 81, 138],
[ 223, 548, 1941, 35],
[ 32, 103, 19, 435]])
Report precision, recall, and f1:
labelsname: label_Cardiomegaly, Label_value 0: 0.981, 0.981, 0.981
labelsname: label_Cardiomegaly, Label_value 1: 0.931, 0.931, 0.931
labelsname: label_Cardiomegaly, Label_value 2: 0.707, 0.707, 0.707
labelsname: label_Cardiomegaly, Label_value 3: 0.739, 0.739, 0.739
Acc. (Correct/Total): 0.9453 (31312/33124)
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 100, Avg loss: 0.276
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 200, Avg loss: 0.179
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 300, Avg loss: 0.234
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 400, Avg loss: 0.200
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 500, Avg loss: 0.233
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 600, Avg loss: 0.222
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 700, Avg loss: 0.189
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 800, Avg loss: 0.176
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 900, Avg loss: 0.209
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 1000, Avg loss: 0.209
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 1100, Avg loss: 0.214
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 1200, Avg loss: 0.186
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 1300, Avg loss: 0.188
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 1400, Avg loss: 0.175
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 1500, Avg loss: 0.202
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 1600, Avg loss: 0.168
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 1700, Avg loss: 0.217
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 1800, Avg loss: 0.226
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 1900, Avg loss: 0.210
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 2000, Avg loss: 0.162
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 2100, Avg loss: 0.224
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 2200, Avg loss: 0.225
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 2300, Avg loss: 0.184
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 2400, Avg loss: 0.182
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 2500, Avg loss: 0.223
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 2600, Avg loss: 0.179
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 2700, Avg loss: 0.174
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 2800, Avg loss: 0.182
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 2900, Avg loss: 0.176
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 3000, Avg loss: 0.185
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 3100, Avg loss: 0.183
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 3200, Avg loss: 0.197
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 3300, Avg loss: 0.217
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 3400, Avg loss: 0.209
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 3500, Avg loss: 0.179
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 3600, Avg loss: 0.193
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 3700, Avg loss: 0.174
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 3800, Avg loss: 0.172
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 3900, Avg loss: 0.155
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 4000, Avg loss: 0.216
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 4100, Avg loss: 0.200
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 4200, Avg loss: 0.188
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 4300, Avg loss: 0.194
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 4400, Avg loss: 0.191
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 4500, Avg loss: 0.189
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 4600, Avg loss: 0.203
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 4700, Avg loss: 0.184
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 4800, Avg loss: 0.204
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 4900, Avg loss: 0.192
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 5000, Avg loss: 0.166
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 5100, Avg loss: 0.220
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 5200, Avg loss: 0.172
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 5300, Avg loss: 0.182
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 5400, Avg loss: 0.169
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 5500, Avg loss: 0.163
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 5600, Avg loss: 0.190
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 5700, Avg loss: 0.189
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 5800, Avg loss: 0.213
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 5900, Avg loss: 0.171
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 6000, Avg loss: 0.179
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 6100, Avg loss: 0.202
labelsname: label_Cardiomegaly, Epoch id: 2, Training steps: 6200, Avg loss: 0.177
Start evaluation on test dataset.
Loading sentences from ./datasets/CheXpert/impression/validation.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
labelsname: label_Cardiomegaly, Label_value 0: 0.978, 0.978, 0.978
labelsname: label_Cardiomegaly, Label_value 1: 0.948, 0.948, 0.948
labelsname: label_Cardiomegaly, Label_value 2: 0.759, 0.759, 0.759
labelsname: label_Cardiomegaly, Label_value 3: 0.720, 0.720, 0.720
Acc. (Correct/Total): 0.9508 (31495/33124)
Start evaluation on evaluation dataset.
Loading sentences from ./datasets/CheXpert/impression/test.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
The number of evaluation instances: 33124
Confusion matrix of {label_name}:
tensor([[23865, 312, 57, 187],
[ 76, 5221, 105, 118],
[ 189, 424, 1905, 19],
[ 25, 144, 22, 455]])
Report precision, recall, and f1:
labelsname: label_Cardiomegaly, Label_value 0: 0.977, 0.977, 0.977
labelsname: label_Cardiomegaly, Label_value 1: 0.946, 0.946, 0.946
labelsname: label_Cardiomegaly, Label_value 2: 0.751, 0.751, 0.751
labelsname: label_Cardiomegaly, Label_value 3: 0.704, 0.704, 0.704
Acc. (Correct/Total): 0.9493 (31446/33124)
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 100, Avg loss: 0.255
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 200, Avg loss: 0.157
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 300, Avg loss: 0.216
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 400, Avg loss: 0.172
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 500, Avg loss: 0.209
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 600, Avg loss: 0.192
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 700, Avg loss: 0.174
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 800, Avg loss: 0.163
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 900, Avg loss: 0.193
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 1000, Avg loss: 0.189
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 1100, Avg loss: 0.184
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 1200, Avg loss: 0.168
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 1300, Avg loss: 0.170
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 1400, Avg loss: 0.167
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 1500, Avg loss: 0.190
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 1600, Avg loss: 0.146
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 1700, Avg loss: 0.190
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 1800, Avg loss: 0.206
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 1900, Avg loss: 0.184
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 2000, Avg loss: 0.149
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 2100, Avg loss: 0.213
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 2200, Avg loss: 0.191
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 2300, Avg loss: 0.164
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 2400, Avg loss: 0.160
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 2500, Avg loss: 0.208
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 2600, Avg loss: 0.164
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 2700, Avg loss: 0.162
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 2800, Avg loss: 0.164
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 2900, Avg loss: 0.157
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 3000, Avg loss: 0.172
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 3100, Avg loss: 0.159
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 3200, Avg loss: 0.181
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 3300, Avg loss: 0.195
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 3400, Avg loss: 0.186
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 3500, Avg loss: 0.167
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 3600, Avg loss: 0.172
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 3700, Avg loss: 0.156
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 3800, Avg loss: 0.162
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 3900, Avg loss: 0.146
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 4000, Avg loss: 0.198
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 4100, Avg loss: 0.179
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 4200, Avg loss: 0.164
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 4300, Avg loss: 0.178
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 4400, Avg loss: 0.168
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 4500, Avg loss: 0.166
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 4600, Avg loss: 0.194
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 4700, Avg loss: 0.173
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 4800, Avg loss: 0.185
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 4900, Avg loss: 0.172
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 5000, Avg loss: 0.146
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 5100, Avg loss: 0.200
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 5200, Avg loss: 0.158
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 5300, Avg loss: 0.173
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 5400, Avg loss: 0.160
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 5500, Avg loss: 0.149
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 5600, Avg loss: 0.191
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 5700, Avg loss: 0.166
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 5800, Avg loss: 0.194
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 5900, Avg loss: 0.162
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 6000, Avg loss: 0.168
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 6100, Avg loss: 0.189
labelsname: label_Cardiomegaly, Epoch id: 3, Training steps: 6200, Avg loss: 0.166
Start evaluation on test dataset.
Loading sentences from ./datasets/CheXpert/impression/validation.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
labelsname: label_Cardiomegaly, Label_value 0: 0.982, 0.982, 0.982
labelsname: label_Cardiomegaly, Label_value 1: 0.933, 0.933, 0.933
labelsname: label_Cardiomegaly, Label_value 2: 0.753, 0.753, 0.753
labelsname: label_Cardiomegaly, Label_value 3: 0.816, 0.816, 0.816
Acc. (Correct/Total): 0.9534 (31579/33124)
Start evaluation on evaluation dataset.
Loading sentences from ./datasets/CheXpert/impression/test.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
The number of evaluation instances: 33124
Confusion matrix of {label_name}:
tensor([[23801, 235, 41, 165],
[ 132, 5377, 100, 156],
[ 201, 431, 1928, 22],
[ 21, 58, 20, 436]])
Report precision, recall, and f1:
labelsname: label_Cardiomegaly, Label_value 0: 0.982, 0.982, 0.982
labelsname: label_Cardiomegaly, Label_value 1: 0.933, 0.933, 0.933
labelsname: label_Cardiomegaly, Label_value 2: 0.747, 0.747, 0.747
labelsname: label_Cardiomegaly, Label_value 3: 0.815, 0.815, 0.815
Acc. (Correct/Total): 0.9522 (31542/33124)
Final evaluation on the evaluation dataset.
Loading sentences from ./datasets/CheXpert/impression/test.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
The number of evaluation instances: 33124
Confusion matrix of {label_name}:
tensor([[23801, 235, 41, 165],
[ 132, 5377, 100, 156],
[ 201, 431, 1928, 22],
[ 21, 58, 20, 436]])
Report precision, recall, and f1:
labelsname: label_Cardiomegaly, Label_value 0: 0.982, 0.982, 0.982
labelsname: label_Cardiomegaly, Label_value 1: 0.933, 0.933, 0.933
labelsname: label_Cardiomegaly, Label_value 2: 0.747, 0.747, 0.747
labelsname: label_Cardiomegaly, Label_value 3: 0.815, 0.815, 0.815
Acc. (Correct/Total): 0.9522 (31542/33124)
labelsname: label_Consolidation, Epoch id: 1, Training steps: 100, Avg loss: 0.856
labelsname: label_Consolidation, Epoch id: 1, Training steps: 200, Avg loss: 0.490
labelsname: label_Consolidation, Epoch id: 1, Training steps: 300, Avg loss: 0.431
labelsname: label_Consolidation, Epoch id: 1, Training steps: 400, Avg loss: 0.402
labelsname: label_Consolidation, Epoch id: 1, Training steps: 500, Avg loss: 0.426
labelsname: label_Consolidation, Epoch id: 1, Training steps: 600, Avg loss: 0.422
labelsname: label_Consolidation, Epoch id: 1, Training steps: 700, Avg loss: 0.378
labelsname: label_Consolidation, Epoch id: 1, Training steps: 800, Avg loss: 0.275
labelsname: label_Consolidation, Epoch id: 1, Training steps: 900, Avg loss: 0.204
labelsname: label_Consolidation, Epoch id: 1, Training steps: 1000, Avg loss: 0.166
labelsname: label_Consolidation, Epoch id: 1, Training steps: 1100, Avg loss: 0.159
labelsname: label_Consolidation, Epoch id: 1, Training steps: 1200, Avg loss: 0.156
labelsname: label_Consolidation, Epoch id: 1, Training steps: 1300, Avg loss: 0.163
labelsname: label_Consolidation, Epoch id: 1, Training steps: 1400, Avg loss: 0.157
labelsname: label_Consolidation, Epoch id: 1, Training steps: 1500, Avg loss: 0.158
labelsname: label_Consolidation, Epoch id: 1, Training steps: 1600, Avg loss: 0.120
labelsname: label_Consolidation, Epoch id: 1, Training steps: 1700, Avg loss: 0.135
labelsname: label_Consolidation, Epoch id: 1, Training steps: 1800, Avg loss: 0.172
labelsname: label_Consolidation, Epoch id: 1, Training steps: 1900, Avg loss: 0.127
labelsname: label_Consolidation, Epoch id: 1, Training steps: 2000, Avg loss: 0.136
labelsname: label_Consolidation, Epoch id: 1, Training steps: 2100, Avg loss: 0.110
labelsname: label_Consolidation, Epoch id: 1, Training steps: 2200, Avg loss: 0.127
labelsname: label_Consolidation, Epoch id: 1, Training steps: 2300, Avg loss: 0.140
labelsname: label_Consolidation, Epoch id: 1, Training steps: 2400, Avg loss: 0.121
labelsname: label_Consolidation, Epoch id: 1, Training steps: 2500, Avg loss: 0.136
labelsname: label_Consolidation, Epoch id: 1, Training steps: 2600, Avg loss: 0.120
labelsname: label_Consolidation, Epoch id: 1, Training steps: 2700, Avg loss: 0.122
labelsname: label_Consolidation, Epoch id: 1, Training steps: 2800, Avg loss: 0.119
labelsname: label_Consolidation, Epoch id: 1, Training steps: 2900, Avg loss: 0.120
labelsname: label_Consolidation, Epoch id: 1, Training steps: 3000, Avg loss: 0.118
labelsname: label_Consolidation, Epoch id: 1, Training steps: 3100, Avg loss: 0.118
labelsname: label_Consolidation, Epoch id: 1, Training steps: 3200, Avg loss: 0.140
labelsname: label_Consolidation, Epoch id: 1, Training steps: 3300, Avg loss: 0.124
labelsname: label_Consolidation, Epoch id: 1, Training steps: 3400, Avg loss: 0.112
labelsname: label_Consolidation, Epoch id: 1, Training steps: 3500, Avg loss: 0.123
labelsname: label_Consolidation, Epoch id: 1, Training steps: 3600, Avg loss: 0.135
labelsname: label_Consolidation, Epoch id: 1, Training steps: 3700, Avg loss: 0.122
labelsname: label_Consolidation, Epoch id: 1, Training steps: 3800, Avg loss: 0.121
labelsname: label_Consolidation, Epoch id: 1, Training steps: 3900, Avg loss: 0.119
labelsname: label_Consolidation, Epoch id: 1, Training steps: 4000, Avg loss: 0.099
labelsname: label_Consolidation, Epoch id: 1, Training steps: 4100, Avg loss: 0.120
labelsname: label_Consolidation, Epoch id: 1, Training steps: 4200, Avg loss: 0.099
labelsname: label_Consolidation, Epoch id: 1, Training steps: 4300, Avg loss: 0.117
labelsname: label_Consolidation, Epoch id: 1, Training steps: 4400, Avg loss: 0.101
labelsname: label_Consolidation, Epoch id: 1, Training steps: 4500, Avg loss: 0.136
labelsname: label_Consolidation, Epoch id: 1, Training steps: 4600, Avg loss: 0.128
labelsname: label_Consolidation, Epoch id: 1, Training steps: 4700, Avg loss: 0.088
labelsname: label_Consolidation, Epoch id: 1, Training steps: 4800, Avg loss: 0.122
labelsname: label_Consolidation, Epoch id: 1, Training steps: 4900, Avg loss: 0.120
labelsname: label_Consolidation, Epoch id: 1, Training steps: 5000, Avg loss: 0.128
labelsname: label_Consolidation, Epoch id: 1, Training steps: 5100, Avg loss: 0.115
labelsname: label_Consolidation, Epoch id: 1, Training steps: 5200, Avg loss: 0.116
labelsname: label_Consolidation, Epoch id: 1, Training steps: 5300, Avg loss: 0.112
labelsname: label_Consolidation, Epoch id: 1, Training steps: 5400, Avg loss: 0.134
labelsname: label_Consolidation, Epoch id: 1, Training steps: 5500, Avg loss: 0.116
labelsname: label_Consolidation, Epoch id: 1, Training steps: 5600, Avg loss: 0.118
labelsname: label_Consolidation, Epoch id: 1, Training steps: 5700, Avg loss: 0.108
labelsname: label_Consolidation, Epoch id: 1, Training steps: 5800, Avg loss: 0.131
labelsname: label_Consolidation, Epoch id: 1, Training steps: 5900, Avg loss: 0.124
labelsname: label_Consolidation, Epoch id: 1, Training steps: 6000, Avg loss: 0.118
labelsname: label_Consolidation, Epoch id: 1, Training steps: 6100, Avg loss: 0.110
labelsname: label_Consolidation, Epoch id: 1, Training steps: 6200, Avg loss: 0.104
Start evaluation on test dataset.
Loading sentences from ./datasets/CheXpert/impression/validation.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
labelsname: label_Consolidation, Label_value 0: 0.993, 1.000, 0.996
labelsname: label_Consolidation, Label_value 1: 0.739, 0.797, 0.766
labelsname: label_Consolidation, Label_value 2: 0.711, 0.880, 0.786
model never predicts label value 3
labelsname: label_Consolidation, Label_value 3: 0.000, 0.000, 0.000
Acc. (Correct/Total): 0.9661 (32002/33124)
Start evaluation on evaluation dataset.
Loading sentences from ./datasets/CheXpert/impression/test.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
The number of evaluation instances: 33124
Confusion matrix of {label_name}:
tensor([[29566, 158, 39, 12],
[ 5, 1341, 109, 401],
[ 3, 190, 1055, 245],
[ 0, 0, 0, 0]])
Report precision, recall, and f1:
labelsname: label_Consolidation, Label_value 0: 0.993, 1.000, 0.996
labelsname: label_Consolidation, Label_value 1: 0.723, 0.794, 0.757
labelsname: label_Consolidation, Label_value 2: 0.707, 0.877, 0.783
model never predicts label value 3
labelsname: label_Consolidation, Label_value 3: 0.000, 0.000, 0.000
Acc. (Correct/Total): 0.9649 (31962/33124)
labelsname: label_Consolidation, Epoch id: 2, Training steps: 100, Avg loss: 0.117
labelsname: label_Consolidation, Epoch id: 2, Training steps: 200, Avg loss: 0.115
labelsname: label_Consolidation, Epoch id: 2, Training steps: 300, Avg loss: 0.139
labelsname: label_Consolidation, Epoch id: 2, Training steps: 400, Avg loss: 0.101
labelsname: label_Consolidation, Epoch id: 2, Training steps: 500, Avg loss: 0.108
labelsname: label_Consolidation, Epoch id: 2, Training steps: 600, Avg loss: 0.133
labelsname: label_Consolidation, Epoch id: 2, Training steps: 700, Avg loss: 0.141
labelsname: label_Consolidation, Epoch id: 2, Training steps: 800, Avg loss: 0.127
labelsname: label_Consolidation, Epoch id: 2, Training steps: 900, Avg loss: 0.123
labelsname: label_Consolidation, Epoch id: 2, Training steps: 1000, Avg loss: 0.103
labelsname: label_Consolidation, Epoch id: 2, Training steps: 1100, Avg loss: 0.121
labelsname: label_Consolidation, Epoch id: 2, Training steps: 1200, Avg loss: 0.118
labelsname: label_Consolidation, Epoch id: 2, Training steps: 1300, Avg loss: 0.111
labelsname: label_Consolidation, Epoch id: 2, Training steps: 1400, Avg loss: 0.111
labelsname: label_Consolidation, Epoch id: 2, Training steps: 1500, Avg loss: 0.134
labelsname: label_Consolidation, Epoch id: 2, Training steps: 1600, Avg loss: 0.093
labelsname: label_Consolidation, Epoch id: 2, Training steps: 1700, Avg loss: 0.097
labelsname: label_Consolidation, Epoch id: 2, Training steps: 1800, Avg loss: 0.123
labelsname: label_Consolidation, Epoch id: 2, Training steps: 1900, Avg loss: 0.101
labelsname: label_Consolidation, Epoch id: 2, Training steps: 2000, Avg loss: 0.112
labelsname: label_Consolidation, Epoch id: 2, Training steps: 2100, Avg loss: 0.081
labelsname: label_Consolidation, Epoch id: 2, Training steps: 2200, Avg loss: 0.109
labelsname: label_Consolidation, Epoch id: 2, Training steps: 2300, Avg loss: 0.121
labelsname: label_Consolidation, Epoch id: 2, Training steps: 2400, Avg loss: 0.098
labelsname: label_Consolidation, Epoch id: 2, Training steps: 2500, Avg loss: 0.121
labelsname: label_Consolidation, Epoch id: 2, Training steps: 2600, Avg loss: 0.104
labelsname: label_Consolidation, Epoch id: 2, Training steps: 2700, Avg loss: 0.116
labelsname: label_Consolidation, Epoch id: 2, Training steps: 2800, Avg loss: 0.106
labelsname: label_Consolidation, Epoch id: 2, Training steps: 2900, Avg loss: 0.107
labelsname: label_Consolidation, Epoch id: 2, Training steps: 3000, Avg loss: 0.107
labelsname: label_Consolidation, Epoch id: 2, Training steps: 3100, Avg loss: 0.108
labelsname: label_Consolidation, Epoch id: 2, Training steps: 3200, Avg loss: 0.125
labelsname: label_Consolidation, Epoch id: 2, Training steps: 3300, Avg loss: 0.114
labelsname: label_Consolidation, Epoch id: 2, Training steps: 3400, Avg loss: 0.100
labelsname: label_Consolidation, Epoch id: 2, Training steps: 3500, Avg loss: 0.109
labelsname: label_Consolidation, Epoch id: 2, Training steps: 3600, Avg loss: 0.124
labelsname: label_Consolidation, Epoch id: 2, Training steps: 3700, Avg loss: 0.116
labelsname: label_Consolidation, Epoch id: 2, Training steps: 3800, Avg loss: 0.111
labelsname: label_Consolidation, Epoch id: 2, Training steps: 3900, Avg loss: 0.116
labelsname: label_Consolidation, Epoch id: 2, Training steps: 4000, Avg loss: 0.090
labelsname: label_Consolidation, Epoch id: 2, Training steps: 4100, Avg loss: 0.103
labelsname: label_Consolidation, Epoch id: 2, Training steps: 4200, Avg loss: 0.095
labelsname: label_Consolidation, Epoch id: 2, Training steps: 4300, Avg loss: 0.104
labelsname: label_Consolidation, Epoch id: 2, Training steps: 4400, Avg loss: 0.088
labelsname: label_Consolidation, Epoch id: 2, Training steps: 4500, Avg loss: 0.123
labelsname: label_Consolidation, Epoch id: 2, Training steps: 4600, Avg loss: 0.119
labelsname: label_Consolidation, Epoch id: 2, Training steps: 4700, Avg loss: 0.076
labelsname: label_Consolidation, Epoch id: 2, Training steps: 4800, Avg loss: 0.107
labelsname: label_Consolidation, Epoch id: 2, Training steps: 4900, Avg loss: 0.104
labelsname: label_Consolidation, Epoch id: 2, Training steps: 5000, Avg loss: 0.111
labelsname: label_Consolidation, Epoch id: 2, Training steps: 5100, Avg loss: 0.105
labelsname: label_Consolidation, Epoch id: 2, Training steps: 5200, Avg loss: 0.108
labelsname: label_Consolidation, Epoch id: 2, Training steps: 5300, Avg loss: 0.099
labelsname: label_Consolidation, Epoch id: 2, Training steps: 5400, Avg loss: 0.123
labelsname: label_Consolidation, Epoch id: 2, Training steps: 5500, Avg loss: 0.104
labelsname: label_Consolidation, Epoch id: 2, Training steps: 5600, Avg loss: 0.106
labelsname: label_Consolidation, Epoch id: 2, Training steps: 5700, Avg loss: 0.096
labelsname: label_Consolidation, Epoch id: 2, Training steps: 5800, Avg loss: 0.121
labelsname: label_Consolidation, Epoch id: 2, Training steps: 5900, Avg loss: 0.111
labelsname: label_Consolidation, Epoch id: 2, Training steps: 6000, Avg loss: 0.115
labelsname: label_Consolidation, Epoch id: 2, Training steps: 6100, Avg loss: 0.099
labelsname: label_Consolidation, Epoch id: 2, Training steps: 6200, Avg loss: 0.094
Start evaluation on test dataset.
Loading sentences from ./datasets/CheXpert/impression/validation.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
labelsname: label_Consolidation, Label_value 0: 0.993, 1.000, 0.996
labelsname: label_Consolidation, Label_value 1: 0.753, 0.800, 0.776
labelsname: label_Consolidation, Label_value 2: 0.770, 0.866, 0.815
labelsname: label_Consolidation, Label_value 3: 0.432, 0.107, 0.172
Acc. (Correct/Total): 0.9679 (32060/33124)
Start evaluation on evaluation dataset.
Loading sentences from ./datasets/CheXpert/impression/test.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
The number of evaluation instances: 33124
Confusion matrix of {label_name}:
tensor([[29567, 159, 40, 12],
[ 4, 1366, 99, 377],
[ 3, 99, 1034, 183],
[ 0, 65, 30, 86]])
Report precision, recall, and f1:
labelsname: label_Consolidation, Label_value 0: 0.993, 1.000, 0.996
labelsname: label_Consolidation, Label_value 1: 0.740, 0.809, 0.773
labelsname: label_Consolidation, Label_value 2: 0.784, 0.860, 0.820
labelsname: label_Consolidation, Label_value 3: 0.475, 0.131, 0.205
Acc. (Correct/Total): 0.9677 (32053/33124)
labelsname: label_Consolidation, Epoch id: 3, Training steps: 100, Avg loss: 0.101
labelsname: label_Consolidation, Epoch id: 3, Training steps: 200, Avg loss: 0.105
labelsname: label_Consolidation, Epoch id: 3, Training steps: 300, Avg loss: 0.118
labelsname: label_Consolidation, Epoch id: 3, Training steps: 400, Avg loss: 0.094
labelsname: label_Consolidation, Epoch id: 3, Training steps: 500, Avg loss: 0.104
labelsname: label_Consolidation, Epoch id: 3, Training steps: 600, Avg loss: 0.118
labelsname: label_Consolidation, Epoch id: 3, Training steps: 700, Avg loss: 0.114
labelsname: label_Consolidation, Epoch id: 3, Training steps: 800, Avg loss: 0.115
labelsname: label_Consolidation, Epoch id: 3, Training steps: 900, Avg loss: 0.116
labelsname: label_Consolidation, Epoch id: 3, Training steps: 1000, Avg loss: 0.090
labelsname: label_Consolidation, Epoch id: 3, Training steps: 1100, Avg loss: 0.108
labelsname: label_Consolidation, Epoch id: 3, Training steps: 1200, Avg loss: 0.109
labelsname: label_Consolidation, Epoch id: 3, Training steps: 1300, Avg loss: 0.104
labelsname: label_Consolidation, Epoch id: 3, Training steps: 1400, Avg loss: 0.098
labelsname: label_Consolidation, Epoch id: 3, Training steps: 1500, Avg loss: 0.130
labelsname: label_Consolidation, Epoch id: 3, Training steps: 1600, Avg loss: 0.086
labelsname: label_Consolidation, Epoch id: 3, Training steps: 1700, Avg loss: 0.088
labelsname: label_Consolidation, Epoch id: 3, Training steps: 1800, Avg loss: 0.109
labelsname: label_Consolidation, Epoch id: 3, Training steps: 1900, Avg loss: 0.089
labelsname: label_Consolidation, Epoch id: 3, Training steps: 2000, Avg loss: 0.103
labelsname: label_Consolidation, Epoch id: 3, Training steps: 2100, Avg loss: 0.070
labelsname: label_Consolidation, Epoch id: 3, Training steps: 2200, Avg loss: 0.101
labelsname: label_Consolidation, Epoch id: 3, Training steps: 2300, Avg loss: 0.115
labelsname: label_Consolidation, Epoch id: 3, Training steps: 2400, Avg loss: 0.091
labelsname: label_Consolidation, Epoch id: 3, Training steps: 2500, Avg loss: 0.113
labelsname: label_Consolidation, Epoch id: 3, Training steps: 2600, Avg loss: 0.090
labelsname: label_Consolidation, Epoch id: 3, Training steps: 2700, Avg loss: 0.107
labelsname: label_Consolidation, Epoch id: 3, Training steps: 2800, Avg loss: 0.096
labelsname: label_Consolidation, Epoch id: 3, Training steps: 2900, Avg loss: 0.094
labelsname: label_Consolidation, Epoch id: 3, Training steps: 3000, Avg loss: 0.091
labelsname: label_Consolidation, Epoch id: 3, Training steps: 3100, Avg loss: 0.098
labelsname: label_Consolidation, Epoch id: 3, Training steps: 3200, Avg loss: 0.107
labelsname: label_Consolidation, Epoch id: 3, Training steps: 3300, Avg loss: 0.101
labelsname: label_Consolidation, Epoch id: 3, Training steps: 3400, Avg loss: 0.091
labelsname: label_Consolidation, Epoch id: 3, Training steps: 3500, Avg loss: 0.096
labelsname: label_Consolidation, Epoch id: 3, Training steps: 3600, Avg loss: 0.111
labelsname: label_Consolidation, Epoch id: 3, Training steps: 3700, Avg loss: 0.110
labelsname: label_Consolidation, Epoch id: 3, Training steps: 3800, Avg loss: 0.097
labelsname: label_Consolidation, Epoch id: 3, Training steps: 3900, Avg loss: 0.105
labelsname: label_Consolidation, Epoch id: 3, Training steps: 4000, Avg loss: 0.082
labelsname: label_Consolidation, Epoch id: 3, Training steps: 4100, Avg loss: 0.091
labelsname: label_Consolidation, Epoch id: 3, Training steps: 4200, Avg loss: 0.087
labelsname: label_Consolidation, Epoch id: 3, Training steps: 4300, Avg loss: 0.093
labelsname: label_Consolidation, Epoch id: 3, Training steps: 4400, Avg loss: 0.077
labelsname: label_Consolidation, Epoch id: 3, Training steps: 4500, Avg loss: 0.113
labelsname: label_Consolidation, Epoch id: 3, Training steps: 4600, Avg loss: 0.107
labelsname: label_Consolidation, Epoch id: 3, Training steps: 4700, Avg loss: 0.067
labelsname: label_Consolidation, Epoch id: 3, Training steps: 4800, Avg loss: 0.095
labelsname: label_Consolidation, Epoch id: 3, Training steps: 4900, Avg loss: 0.094
labelsname: label_Consolidation, Epoch id: 3, Training steps: 5000, Avg loss: 0.100
labelsname: label_Consolidation, Epoch id: 3, Training steps: 5100, Avg loss: 0.090
labelsname: label_Consolidation, Epoch id: 3, Training steps: 5200, Avg loss: 0.101
labelsname: label_Consolidation, Epoch id: 3, Training steps: 5300, Avg loss: 0.088
labelsname: label_Consolidation, Epoch id: 3, Training steps: 5400, Avg loss: 0.118
labelsname: label_Consolidation, Epoch id: 3, Training steps: 5500, Avg loss: 0.089
labelsname: label_Consolidation, Epoch id: 3, Training steps: 5600, Avg loss: 0.096
labelsname: label_Consolidation, Epoch id: 3, Training steps: 5700, Avg loss: 0.085
labelsname: label_Consolidation, Epoch id: 3, Training steps: 5800, Avg loss: 0.106
labelsname: label_Consolidation, Epoch id: 3, Training steps: 5900, Avg loss: 0.105
labelsname: label_Consolidation, Epoch id: 3, Training steps: 6000, Avg loss: 0.105
labelsname: label_Consolidation, Epoch id: 3, Training steps: 6100, Avg loss: 0.092
labelsname: label_Consolidation, Epoch id: 3, Training steps: 6200, Avg loss: 0.089
Start evaluation on test dataset.
Loading sentences from ./datasets/CheXpert/impression/validation.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
labelsname: label_Consolidation, Label_value 0: 0.993, 1.000, 0.996
labelsname: label_Consolidation, Label_value 1: 0.779, 0.804, 0.791
labelsname: label_Consolidation, Label_value 2: 0.779, 0.883, 0.828
labelsname: label_Consolidation, Label_value 3: 0.683, 0.218, 0.330
Acc. (Correct/Total): 0.9708 (32157/33124)
Start evaluation on evaluation dataset.
Loading sentences from ./datasets/CheXpert/impression/test.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
The number of evaluation instances: 33124
Confusion matrix of {label_name}:
tensor([[29567, 158, 40, 12],
[ 4, 1362, 96, 356],
[ 3, 112, 1047, 170],
[ 0, 57, 20, 120]])
Report precision, recall, and f1:
labelsname: label_Consolidation, Label_value 0: 0.993, 1.000, 0.996
labelsname: label_Consolidation, Label_value 1: 0.749, 0.806, 0.777
labelsname: label_Consolidation, Label_value 2: 0.786, 0.870, 0.826
labelsname: label_Consolidation, Label_value 3: 0.609, 0.182, 0.281
Acc. (Correct/Total): 0.9690 (32096/33124)
Final evaluation on the evaluation dataset.
Loading sentences from ./datasets/CheXpert/impression/test.csv
There are 33124 sentence in total. We use 1 processes to inject knowledge into sentences.
Progress of process 0: 0/33124
Progress of process 0: 10000/33124
Progress of process 0: 20000/33124
Progress of process 0: 30000/33124
The number of evaluation instances: 33124
Confusion matrix of {label_name}:
tensor([[29567, 158, 40, 12],
[ 4, 1362, 96, 356],
[ 3, 112, 1047, 170],
[ 0, 57, 20, 120]])
Report precision, recall, and f1:
labelsname: label_Consolidation, Label_value 0: 0.993, 1.000, 0.996
labelsname: label_Consolidation, Label_value 1: 0.749, 0.806, 0.777
labelsname: label_Consolidation, Label_value 2: 0.786, 0.870, 0.826
labelsname: label_Consolidation, Label_value 3: 0.609, 0.182, 0.281
Acc. (Correct/Total): 0.9690 (32096/33124)