End of training
Browse files- README.md +2 -0
- all_results.json +16 -16
- eval_results.json +8 -8
- predict_results.json +4 -4
- predict_results.txt +53 -53
- runs/Jun03_14-28-41_a358b85c7679/events.out.tfevents.1717425557.a358b85c7679.140888.1 +3 -0
- train_results.json +4 -4
- trainer_state.json +204 -204
README.md
CHANGED
@@ -1,4 +1,6 @@
|
|
1 |
---
|
|
|
|
|
2 |
license: mit
|
3 |
base_model: indolem/indobert-base-uncased
|
4 |
tags:
|
|
|
1 |
---
|
2 |
+
language:
|
3 |
+
- id
|
4 |
license: mit
|
5 |
base_model: indolem/indobert-base-uncased
|
6 |
tags:
|
all_results.json
CHANGED
@@ -1,21 +1,21 @@
|
|
1 |
{
|
2 |
-
"accuracy": 0.
|
3 |
"epoch": 20.0,
|
4 |
-
"eval_accuracy": 0.
|
5 |
-
"eval_f1": 0.
|
6 |
-
"eval_loss": 0.
|
7 |
-
"eval_precision": 0.
|
8 |
-
"eval_recall": 0.
|
9 |
-
"eval_runtime":
|
10 |
"eval_samples": 399,
|
11 |
-
"eval_samples_per_second":
|
12 |
-
"eval_steps_per_second":
|
13 |
-
"f1": 0.
|
14 |
-
"precision": 0.
|
15 |
-
"recall": 0.
|
16 |
-
"train_loss": 0.
|
17 |
-
"train_runtime":
|
18 |
"train_samples": 3638,
|
19 |
-
"train_samples_per_second":
|
20 |
-
"train_steps_per_second":
|
21 |
}
|
|
|
1 |
{
|
2 |
+
"accuracy": 0.904055390702275,
|
3 |
"epoch": 20.0,
|
4 |
+
"eval_accuracy": 0.8822055137844611,
|
5 |
+
"eval_f1": 0.858259325044405,
|
6 |
+
"eval_loss": 0.3389217257499695,
|
7 |
+
"eval_precision": 0.8573798178418481,
|
8 |
+
"eval_recall": 0.8591562102200401,
|
9 |
+
"eval_runtime": 1.811,
|
10 |
"eval_samples": 399,
|
11 |
+
"eval_samples_per_second": 220.315,
|
12 |
+
"eval_steps_per_second": 27.608,
|
13 |
+
"f1": 0.8862491460015474,
|
14 |
+
"precision": 0.881173503483252,
|
15 |
+
"recall": 0.8919373664542485,
|
16 |
+
"train_loss": 0.22970127551282038,
|
17 |
+
"train_runtime": 621.3103,
|
18 |
"train_samples": 3638,
|
19 |
+
"train_samples_per_second": 117.107,
|
20 |
+
"train_steps_per_second": 3.927
|
21 |
}
|
eval_results.json
CHANGED
@@ -1,12 +1,12 @@
|
|
1 |
{
|
2 |
"epoch": 20.0,
|
3 |
-
"eval_accuracy": 0.
|
4 |
-
"eval_f1": 0.
|
5 |
-
"eval_loss": 0.
|
6 |
-
"eval_precision": 0.
|
7 |
-
"eval_recall": 0.
|
8 |
-
"eval_runtime":
|
9 |
"eval_samples": 399,
|
10 |
-
"eval_samples_per_second":
|
11 |
-
"eval_steps_per_second":
|
12 |
}
|
|
|
1 |
{
|
2 |
"epoch": 20.0,
|
3 |
+
"eval_accuracy": 0.8822055137844611,
|
4 |
+
"eval_f1": 0.858259325044405,
|
5 |
+
"eval_loss": 0.3389217257499695,
|
6 |
+
"eval_precision": 0.8573798178418481,
|
7 |
+
"eval_recall": 0.8591562102200401,
|
8 |
+
"eval_runtime": 1.811,
|
9 |
"eval_samples": 399,
|
10 |
+
"eval_samples_per_second": 220.315,
|
11 |
+
"eval_steps_per_second": 27.608
|
12 |
}
|
predict_results.json
CHANGED
@@ -1,6 +1,6 @@
|
|
1 |
{
|
2 |
-
"accuracy": 0.
|
3 |
-
"f1": 0.
|
4 |
-
"precision": 0.
|
5 |
-
"recall": 0.
|
6 |
}
|
|
|
1 |
{
|
2 |
+
"accuracy": 0.904055390702275,
|
3 |
+
"f1": 0.8862491460015474,
|
4 |
+
"precision": 0.881173503483252,
|
5 |
+
"recall": 0.8919373664542485
|
6 |
}
|
predict_results.txt
CHANGED
@@ -13,14 +13,14 @@ index prediction
|
|
13 |
11 1
|
14 |
12 1
|
15 |
13 0
|
16 |
-
14
|
17 |
15 1
|
18 |
16 1
|
19 |
17 1
|
20 |
18 1
|
21 |
19 1
|
22 |
20 1
|
23 |
-
21
|
24 |
22 1
|
25 |
23 1
|
26 |
24 1
|
@@ -30,13 +30,13 @@ index prediction
|
|
30 |
28 1
|
31 |
29 1
|
32 |
30 1
|
33 |
-
31
|
34 |
32 1
|
35 |
33 1
|
36 |
34 1
|
37 |
35 1
|
38 |
36 1
|
39 |
-
37
|
40 |
38 1
|
41 |
39 1
|
42 |
40 1
|
@@ -58,7 +58,7 @@ index prediction
|
|
58 |
56 1
|
59 |
57 1
|
60 |
58 1
|
61 |
-
59
|
62 |
60 1
|
63 |
61 1
|
64 |
62 0
|
@@ -75,7 +75,7 @@ index prediction
|
|
75 |
73 1
|
76 |
74 1
|
77 |
75 1
|
78 |
-
76
|
79 |
77 1
|
80 |
78 0
|
81 |
79 1
|
@@ -94,7 +94,7 @@ index prediction
|
|
94 |
92 1
|
95 |
93 1
|
96 |
94 1
|
97 |
-
95
|
98 |
96 1
|
99 |
97 1
|
100 |
98 1
|
@@ -105,10 +105,10 @@ index prediction
|
|
105 |
103 1
|
106 |
104 1
|
107 |
105 0
|
108 |
-
106
|
109 |
107 1
|
110 |
108 1
|
111 |
-
109
|
112 |
110 1
|
113 |
111 1
|
114 |
112 1
|
@@ -116,7 +116,7 @@ index prediction
|
|
116 |
114 1
|
117 |
115 1
|
118 |
116 1
|
119 |
-
117
|
120 |
118 1
|
121 |
119 1
|
122 |
120 1
|
@@ -128,7 +128,7 @@ index prediction
|
|
128 |
126 1
|
129 |
127 1
|
130 |
128 1
|
131 |
-
129
|
132 |
130 1
|
133 |
131 1
|
134 |
132 1
|
@@ -144,16 +144,16 @@ index prediction
|
|
144 |
142 1
|
145 |
143 1
|
146 |
144 1
|
147 |
-
145
|
148 |
146 1
|
149 |
147 1
|
150 |
148 1
|
151 |
149 1
|
152 |
150 1
|
153 |
-
151
|
154 |
152 1
|
155 |
153 1
|
156 |
-
154
|
157 |
155 1
|
158 |
156 0
|
159 |
157 1
|
@@ -162,7 +162,7 @@ index prediction
|
|
162 |
160 1
|
163 |
161 0
|
164 |
162 1
|
165 |
-
163
|
166 |
164 1
|
167 |
165 1
|
168 |
166 0
|
@@ -186,10 +186,10 @@ index prediction
|
|
186 |
184 1
|
187 |
185 1
|
188 |
186 1
|
189 |
-
187
|
190 |
188 1
|
191 |
189 0
|
192 |
-
190
|
193 |
191 1
|
194 |
192 1
|
195 |
193 0
|
@@ -217,7 +217,7 @@ index prediction
|
|
217 |
215 0
|
218 |
216 1
|
219 |
217 0
|
220 |
-
218
|
221 |
219 1
|
222 |
220 1
|
223 |
221 1
|
@@ -232,7 +232,7 @@ index prediction
|
|
232 |
230 0
|
233 |
231 1
|
234 |
232 1
|
235 |
-
233
|
236 |
234 1
|
237 |
235 1
|
238 |
236 1
|
@@ -272,7 +272,7 @@ index prediction
|
|
272 |
270 1
|
273 |
271 0
|
274 |
272 1
|
275 |
-
273
|
276 |
274 1
|
277 |
275 1
|
278 |
276 1
|
@@ -286,9 +286,9 @@ index prediction
|
|
286 |
284 1
|
287 |
285 1
|
288 |
286 1
|
289 |
-
287
|
290 |
288 1
|
291 |
-
289
|
292 |
290 1
|
293 |
291 1
|
294 |
292 1
|
@@ -302,7 +302,7 @@ index prediction
|
|
302 |
300 0
|
303 |
301 0
|
304 |
302 0
|
305 |
-
303
|
306 |
304 0
|
307 |
305 0
|
308 |
306 0
|
@@ -312,7 +312,7 @@ index prediction
|
|
312 |
310 0
|
313 |
311 0
|
314 |
312 0
|
315 |
-
313
|
316 |
314 0
|
317 |
315 0
|
318 |
316 0
|
@@ -338,10 +338,10 @@ index prediction
|
|
338 |
336 0
|
339 |
337 0
|
340 |
338 0
|
341 |
-
339
|
342 |
340 0
|
343 |
341 0
|
344 |
-
342
|
345 |
343 0
|
346 |
344 0
|
347 |
345 0
|
@@ -363,7 +363,7 @@ index prediction
|
|
363 |
361 0
|
364 |
362 0
|
365 |
363 0
|
366 |
-
364
|
367 |
365 0
|
368 |
366 0
|
369 |
367 0
|
@@ -377,7 +377,7 @@ index prediction
|
|
377 |
375 0
|
378 |
376 0
|
379 |
377 0
|
380 |
-
378
|
381 |
379 0
|
382 |
380 0
|
383 |
381 0
|
@@ -419,9 +419,9 @@ index prediction
|
|
419 |
417 0
|
420 |
418 0
|
421 |
419 0
|
422 |
-
420
|
423 |
421 0
|
424 |
-
422
|
425 |
423 0
|
426 |
424 0
|
427 |
425 0
|
@@ -463,7 +463,7 @@ index prediction
|
|
463 |
461 0
|
464 |
462 0
|
465 |
463 0
|
466 |
-
464
|
467 |
465 0
|
468 |
466 0
|
469 |
467 0
|
@@ -472,7 +472,7 @@ index prediction
|
|
472 |
470 0
|
473 |
471 0
|
474 |
472 1
|
475 |
-
473
|
476 |
474 1
|
477 |
475 0
|
478 |
476 1
|
@@ -538,7 +538,7 @@ index prediction
|
|
538 |
536 0
|
539 |
537 0
|
540 |
538 0
|
541 |
-
539
|
542 |
540 0
|
543 |
541 0
|
544 |
542 0
|
@@ -601,7 +601,7 @@ index prediction
|
|
601 |
599 0
|
602 |
600 0
|
603 |
601 0
|
604 |
-
602
|
605 |
603 0
|
606 |
604 0
|
607 |
605 1
|
@@ -621,7 +621,7 @@ index prediction
|
|
621 |
619 0
|
622 |
620 0
|
623 |
621 0
|
624 |
-
622
|
625 |
623 0
|
626 |
624 0
|
627 |
625 0
|
@@ -672,8 +672,8 @@ index prediction
|
|
672 |
670 0
|
673 |
671 0
|
674 |
672 0
|
675 |
-
673
|
676 |
-
674
|
677 |
675 0
|
678 |
676 0
|
679 |
677 0
|
@@ -688,7 +688,7 @@ index prediction
|
|
688 |
686 0
|
689 |
687 0
|
690 |
688 0
|
691 |
-
689
|
692 |
690 0
|
693 |
691 0
|
694 |
692 0
|
@@ -740,7 +740,7 @@ index prediction
|
|
740 |
738 0
|
741 |
739 0
|
742 |
740 0
|
743 |
-
741
|
744 |
742 0
|
745 |
743 0
|
746 |
744 0
|
@@ -784,7 +784,7 @@ index prediction
|
|
784 |
782 0
|
785 |
783 0
|
786 |
784 0
|
787 |
-
785
|
788 |
786 0
|
789 |
787 0
|
790 |
788 0
|
@@ -797,19 +797,19 @@ index prediction
|
|
797 |
795 1
|
798 |
796 0
|
799 |
797 0
|
800 |
-
798
|
801 |
-
799
|
802 |
800 0
|
803 |
801 0
|
804 |
-
802
|
805 |
803 0
|
806 |
804 0
|
807 |
805 0
|
808 |
806 0
|
809 |
807 0
|
810 |
808 0
|
811 |
-
809
|
812 |
-
810
|
813 |
811 0
|
814 |
812 0
|
815 |
813 0
|
@@ -831,7 +831,7 @@ index prediction
|
|
831 |
829 0
|
832 |
830 0
|
833 |
831 1
|
834 |
-
832
|
835 |
833 0
|
836 |
834 0
|
837 |
835 0
|
@@ -859,7 +859,7 @@ index prediction
|
|
859 |
857 1
|
860 |
858 0
|
861 |
859 0
|
862 |
-
860
|
863 |
861 0
|
864 |
862 0
|
865 |
863 0
|
@@ -885,7 +885,7 @@ index prediction
|
|
885 |
883 0
|
886 |
884 0
|
887 |
885 0
|
888 |
-
886
|
889 |
887 0
|
890 |
888 0
|
891 |
889 0
|
@@ -912,7 +912,7 @@ index prediction
|
|
912 |
910 0
|
913 |
911 0
|
914 |
912 1
|
915 |
-
913
|
916 |
914 0
|
917 |
915 0
|
918 |
916 0
|
@@ -923,12 +923,12 @@ index prediction
|
|
923 |
921 1
|
924 |
922 0
|
925 |
923 0
|
926 |
-
924
|
927 |
925 0
|
928 |
926 1
|
929 |
927 0
|
930 |
928 0
|
931 |
-
929
|
932 |
930 0
|
933 |
931 0
|
934 |
932 0
|
@@ -946,7 +946,7 @@ index prediction
|
|
946 |
944 0
|
947 |
945 1
|
948 |
946 0
|
949 |
-
947
|
950 |
948 0
|
951 |
949 0
|
952 |
950 0
|
@@ -966,7 +966,7 @@ index prediction
|
|
966 |
964 0
|
967 |
965 0
|
968 |
966 0
|
969 |
-
967
|
970 |
968 0
|
971 |
969 0
|
972 |
970 0
|
|
|
13 |
11 1
|
14 |
12 1
|
15 |
13 0
|
16 |
+
14 1
|
17 |
15 1
|
18 |
16 1
|
19 |
17 1
|
20 |
18 1
|
21 |
19 1
|
22 |
20 1
|
23 |
+
21 1
|
24 |
22 1
|
25 |
23 1
|
26 |
24 1
|
|
|
30 |
28 1
|
31 |
29 1
|
32 |
30 1
|
33 |
+
31 1
|
34 |
32 1
|
35 |
33 1
|
36 |
34 1
|
37 |
35 1
|
38 |
36 1
|
39 |
+
37 1
|
40 |
38 1
|
41 |
39 1
|
42 |
40 1
|
|
|
58 |
56 1
|
59 |
57 1
|
60 |
58 1
|
61 |
+
59 1
|
62 |
60 1
|
63 |
61 1
|
64 |
62 0
|
|
|
75 |
73 1
|
76 |
74 1
|
77 |
75 1
|
78 |
+
76 1
|
79 |
77 1
|
80 |
78 0
|
81 |
79 1
|
|
|
94 |
92 1
|
95 |
93 1
|
96 |
94 1
|
97 |
+
95 0
|
98 |
96 1
|
99 |
97 1
|
100 |
98 1
|
|
|
105 |
103 1
|
106 |
104 1
|
107 |
105 0
|
108 |
+
106 0
|
109 |
107 1
|
110 |
108 1
|
111 |
+
109 0
|
112 |
110 1
|
113 |
111 1
|
114 |
112 1
|
|
|
116 |
114 1
|
117 |
115 1
|
118 |
116 1
|
119 |
+
117 0
|
120 |
118 1
|
121 |
119 1
|
122 |
120 1
|
|
|
128 |
126 1
|
129 |
127 1
|
130 |
128 1
|
131 |
+
129 1
|
132 |
130 1
|
133 |
131 1
|
134 |
132 1
|
|
|
144 |
142 1
|
145 |
143 1
|
146 |
144 1
|
147 |
+
145 0
|
148 |
146 1
|
149 |
147 1
|
150 |
148 1
|
151 |
149 1
|
152 |
150 1
|
153 |
+
151 0
|
154 |
152 1
|
155 |
153 1
|
156 |
+
154 1
|
157 |
155 1
|
158 |
156 0
|
159 |
157 1
|
|
|
162 |
160 1
|
163 |
161 0
|
164 |
162 1
|
165 |
+
163 0
|
166 |
164 1
|
167 |
165 1
|
168 |
166 0
|
|
|
186 |
184 1
|
187 |
185 1
|
188 |
186 1
|
189 |
+
187 0
|
190 |
188 1
|
191 |
189 0
|
192 |
+
190 0
|
193 |
191 1
|
194 |
192 1
|
195 |
193 0
|
|
|
217 |
215 0
|
218 |
216 1
|
219 |
217 0
|
220 |
+
218 1
|
221 |
219 1
|
222 |
220 1
|
223 |
221 1
|
|
|
232 |
230 0
|
233 |
231 1
|
234 |
232 1
|
235 |
+
233 1
|
236 |
234 1
|
237 |
235 1
|
238 |
236 1
|
|
|
272 |
270 1
|
273 |
271 0
|
274 |
272 1
|
275 |
+
273 1
|
276 |
274 1
|
277 |
275 1
|
278 |
276 1
|
|
|
286 |
284 1
|
287 |
285 1
|
288 |
286 1
|
289 |
+
287 1
|
290 |
288 1
|
291 |
+
289 1
|
292 |
290 1
|
293 |
291 1
|
294 |
292 1
|
|
|
302 |
300 0
|
303 |
301 0
|
304 |
302 0
|
305 |
+
303 1
|
306 |
304 0
|
307 |
305 0
|
308 |
306 0
|
|
|
312 |
310 0
|
313 |
311 0
|
314 |
312 0
|
315 |
+
313 0
|
316 |
314 0
|
317 |
315 0
|
318 |
316 0
|
|
|
338 |
336 0
|
339 |
337 0
|
340 |
338 0
|
341 |
+
339 0
|
342 |
340 0
|
343 |
341 0
|
344 |
+
342 0
|
345 |
343 0
|
346 |
344 0
|
347 |
345 0
|
|
|
363 |
361 0
|
364 |
362 0
|
365 |
363 0
|
366 |
+
364 0
|
367 |
365 0
|
368 |
366 0
|
369 |
367 0
|
|
|
377 |
375 0
|
378 |
376 0
|
379 |
377 0
|
380 |
+
378 0
|
381 |
379 0
|
382 |
380 0
|
383 |
381 0
|
|
|
419 |
417 0
|
420 |
418 0
|
421 |
419 0
|
422 |
+
420 1
|
423 |
421 0
|
424 |
+
422 1
|
425 |
423 0
|
426 |
424 0
|
427 |
425 0
|
|
|
463 |
461 0
|
464 |
462 0
|
465 |
463 0
|
466 |
+
464 0
|
467 |
465 0
|
468 |
466 0
|
469 |
467 0
|
|
|
472 |
470 0
|
473 |
471 0
|
474 |
472 1
|
475 |
+
473 1
|
476 |
474 1
|
477 |
475 0
|
478 |
476 1
|
|
|
538 |
536 0
|
539 |
537 0
|
540 |
538 0
|
541 |
+
539 1
|
542 |
540 0
|
543 |
541 0
|
544 |
542 0
|
|
|
601 |
599 0
|
602 |
600 0
|
603 |
601 0
|
604 |
+
602 1
|
605 |
603 0
|
606 |
604 0
|
607 |
605 1
|
|
|
621 |
619 0
|
622 |
620 0
|
623 |
621 0
|
624 |
+
622 1
|
625 |
623 0
|
626 |
624 0
|
627 |
625 0
|
|
|
672 |
670 0
|
673 |
671 0
|
674 |
672 0
|
675 |
+
673 1
|
676 |
+
674 1
|
677 |
675 0
|
678 |
676 0
|
679 |
677 0
|
|
|
688 |
686 0
|
689 |
687 0
|
690 |
688 0
|
691 |
+
689 0
|
692 |
690 0
|
693 |
691 0
|
694 |
692 0
|
|
|
740 |
738 0
|
741 |
739 0
|
742 |
740 0
|
743 |
+
741 1
|
744 |
742 0
|
745 |
743 0
|
746 |
744 0
|
|
|
784 |
782 0
|
785 |
783 0
|
786 |
784 0
|
787 |
+
785 1
|
788 |
786 0
|
789 |
787 0
|
790 |
788 0
|
|
|
797 |
795 1
|
798 |
796 0
|
799 |
797 0
|
800 |
+
798 0
|
801 |
+
799 0
|
802 |
800 0
|
803 |
801 0
|
804 |
+
802 1
|
805 |
803 0
|
806 |
804 0
|
807 |
805 0
|
808 |
806 0
|
809 |
807 0
|
810 |
808 0
|
811 |
+
809 1
|
812 |
+
810 0
|
813 |
811 0
|
814 |
812 0
|
815 |
813 0
|
|
|
831 |
829 0
|
832 |
830 0
|
833 |
831 1
|
834 |
+
832 0
|
835 |
833 0
|
836 |
834 0
|
837 |
835 0
|
|
|
859 |
857 1
|
860 |
858 0
|
861 |
859 0
|
862 |
+
860 1
|
863 |
861 0
|
864 |
862 0
|
865 |
863 0
|
|
|
885 |
883 0
|
886 |
884 0
|
887 |
885 0
|
888 |
+
886 0
|
889 |
887 0
|
890 |
888 0
|
891 |
889 0
|
|
|
912 |
910 0
|
913 |
911 0
|
914 |
912 1
|
915 |
+
913 0
|
916 |
914 0
|
917 |
915 0
|
918 |
916 0
|
|
|
923 |
921 1
|
924 |
922 0
|
925 |
923 0
|
926 |
+
924 0
|
927 |
925 0
|
928 |
926 1
|
929 |
927 0
|
930 |
928 0
|
931 |
+
929 1
|
932 |
930 0
|
933 |
931 0
|
934 |
932 0
|
|
|
946 |
944 0
|
947 |
945 1
|
948 |
946 0
|
949 |
+
947 1
|
950 |
948 0
|
951 |
949 0
|
952 |
950 0
|
|
|
966 |
964 0
|
967 |
965 0
|
968 |
966 0
|
969 |
+
967 1
|
970 |
968 0
|
971 |
969 0
|
972 |
970 0
|
runs/Jun03_14-28-41_a358b85c7679/events.out.tfevents.1717425557.a358b85c7679.140888.1
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:fa2ba2793098dc75e6508b9c16edb8322d39b79e4617f6dc1fa57a06ee056028
|
3 |
+
size 560
|
train_results.json
CHANGED
@@ -1,8 +1,8 @@
|
|
1 |
{
|
2 |
"epoch": 20.0,
|
3 |
-
"train_loss": 0.
|
4 |
-
"train_runtime":
|
5 |
"train_samples": 3638,
|
6 |
-
"train_samples_per_second":
|
7 |
-
"train_steps_per_second":
|
8 |
}
|
|
|
1 |
{
|
2 |
"epoch": 20.0,
|
3 |
+
"train_loss": 0.22970127551282038,
|
4 |
+
"train_runtime": 621.3103,
|
5 |
"train_samples": 3638,
|
6 |
+
"train_samples_per_second": 117.107,
|
7 |
+
"train_steps_per_second": 3.927
|
8 |
}
|
trainer_state.json
CHANGED
@@ -10,392 +10,392 @@
|
|
10 |
"log_history": [
|
11 |
{
|
12 |
"epoch": 1.0,
|
13 |
-
"grad_norm":
|
14 |
"learning_rate": 4.75e-05,
|
15 |
-
"loss": 0.
|
16 |
"step": 122
|
17 |
},
|
18 |
{
|
19 |
"epoch": 1.0,
|
20 |
-
"eval_accuracy": 0.
|
21 |
-
"eval_f1": 0.
|
22 |
-
"eval_loss": 0.
|
23 |
-
"eval_precision": 0.
|
24 |
-
"eval_recall": 0.
|
25 |
-
"eval_runtime":
|
26 |
-
"eval_samples_per_second":
|
27 |
-
"eval_steps_per_second":
|
28 |
"step": 122
|
29 |
},
|
30 |
{
|
31 |
"epoch": 2.0,
|
32 |
-
"grad_norm": 3.
|
33 |
"learning_rate": 4.5e-05,
|
34 |
-
"loss": 0.
|
35 |
"step": 244
|
36 |
},
|
37 |
{
|
38 |
"epoch": 2.0,
|
39 |
-
"eval_accuracy": 0.
|
40 |
-
"eval_f1": 0.
|
41 |
-
"eval_loss": 0.
|
42 |
-
"eval_precision": 0.
|
43 |
-
"eval_recall": 0.
|
44 |
-
"eval_runtime":
|
45 |
-
"eval_samples_per_second":
|
46 |
-
"eval_steps_per_second":
|
47 |
"step": 244
|
48 |
},
|
49 |
{
|
50 |
"epoch": 3.0,
|
51 |
-
"grad_norm": 3.
|
52 |
"learning_rate": 4.25e-05,
|
53 |
-
"loss": 0.
|
54 |
"step": 366
|
55 |
},
|
56 |
{
|
57 |
"epoch": 3.0,
|
58 |
-
"eval_accuracy": 0.
|
59 |
-
"eval_f1": 0.
|
60 |
-
"eval_loss": 0.
|
61 |
-
"eval_precision": 0.
|
62 |
-
"eval_recall": 0.
|
63 |
-
"eval_runtime":
|
64 |
-
"eval_samples_per_second":
|
65 |
-
"eval_steps_per_second":
|
66 |
"step": 366
|
67 |
},
|
68 |
{
|
69 |
"epoch": 4.0,
|
70 |
-
"grad_norm":
|
71 |
"learning_rate": 4e-05,
|
72 |
-
"loss": 0.
|
73 |
"step": 488
|
74 |
},
|
75 |
{
|
76 |
"epoch": 4.0,
|
77 |
-
"eval_accuracy": 0.
|
78 |
-
"eval_f1": 0.
|
79 |
-
"eval_loss": 0.
|
80 |
-
"eval_precision": 0.
|
81 |
-
"eval_recall": 0.
|
82 |
-
"eval_runtime":
|
83 |
-
"eval_samples_per_second":
|
84 |
-
"eval_steps_per_second":
|
85 |
"step": 488
|
86 |
},
|
87 |
{
|
88 |
"epoch": 5.0,
|
89 |
-
"grad_norm":
|
90 |
"learning_rate": 3.7500000000000003e-05,
|
91 |
-
"loss": 0.
|
92 |
"step": 610
|
93 |
},
|
94 |
{
|
95 |
"epoch": 5.0,
|
96 |
-
"eval_accuracy": 0.
|
97 |
-
"eval_f1": 0.
|
98 |
-
"eval_loss": 0.
|
99 |
-
"eval_precision": 0.
|
100 |
-
"eval_recall": 0.
|
101 |
-
"eval_runtime":
|
102 |
-
"eval_samples_per_second":
|
103 |
-
"eval_steps_per_second":
|
104 |
"step": 610
|
105 |
},
|
106 |
{
|
107 |
"epoch": 6.0,
|
108 |
-
"grad_norm":
|
109 |
"learning_rate": 3.5e-05,
|
110 |
-
"loss": 0.
|
111 |
"step": 732
|
112 |
},
|
113 |
{
|
114 |
"epoch": 6.0,
|
115 |
-
"eval_accuracy": 0.
|
116 |
-
"eval_f1": 0.
|
117 |
-
"eval_loss": 0.
|
118 |
-
"eval_precision": 0.
|
119 |
-
"eval_recall": 0.
|
120 |
-
"eval_runtime":
|
121 |
-
"eval_samples_per_second":
|
122 |
-
"eval_steps_per_second":
|
123 |
"step": 732
|
124 |
},
|
125 |
{
|
126 |
"epoch": 7.0,
|
127 |
-
"grad_norm":
|
128 |
"learning_rate": 3.2500000000000004e-05,
|
129 |
-
"loss": 0.
|
130 |
"step": 854
|
131 |
},
|
132 |
{
|
133 |
"epoch": 7.0,
|
134 |
-
"eval_accuracy": 0.
|
135 |
-
"eval_f1": 0.
|
136 |
-
"eval_loss": 0.
|
137 |
-
"eval_precision": 0.
|
138 |
-
"eval_recall": 0.
|
139 |
-
"eval_runtime":
|
140 |
-
"eval_samples_per_second":
|
141 |
-
"eval_steps_per_second":
|
142 |
"step": 854
|
143 |
},
|
144 |
{
|
145 |
"epoch": 8.0,
|
146 |
-
"grad_norm": 1.
|
147 |
"learning_rate": 3e-05,
|
148 |
-
"loss": 0.
|
149 |
"step": 976
|
150 |
},
|
151 |
{
|
152 |
"epoch": 8.0,
|
153 |
-
"eval_accuracy": 0.
|
154 |
-
"eval_f1": 0.
|
155 |
-
"eval_loss": 0.
|
156 |
-
"eval_precision": 0.
|
157 |
-
"eval_recall": 0.
|
158 |
-
"eval_runtime":
|
159 |
-
"eval_samples_per_second":
|
160 |
-
"eval_steps_per_second":
|
161 |
"step": 976
|
162 |
},
|
163 |
{
|
164 |
"epoch": 9.0,
|
165 |
-
"grad_norm": 5.
|
166 |
"learning_rate": 2.7500000000000004e-05,
|
167 |
-
"loss": 0.
|
168 |
"step": 1098
|
169 |
},
|
170 |
{
|
171 |
"epoch": 9.0,
|
172 |
-
"eval_accuracy": 0.
|
173 |
-
"eval_f1": 0.
|
174 |
-
"eval_loss": 0.
|
175 |
-
"eval_precision": 0.
|
176 |
-
"eval_recall": 0.
|
177 |
-
"eval_runtime":
|
178 |
-
"eval_samples_per_second":
|
179 |
-
"eval_steps_per_second":
|
180 |
"step": 1098
|
181 |
},
|
182 |
{
|
183 |
"epoch": 10.0,
|
184 |
-
"grad_norm":
|
185 |
"learning_rate": 2.5e-05,
|
186 |
-
"loss": 0.
|
187 |
"step": 1220
|
188 |
},
|
189 |
{
|
190 |
"epoch": 10.0,
|
191 |
-
"eval_accuracy": 0.
|
192 |
-
"eval_f1": 0.
|
193 |
-
"eval_loss": 0.
|
194 |
-
"eval_precision": 0.
|
195 |
-
"eval_recall": 0.
|
196 |
-
"eval_runtime":
|
197 |
-
"eval_samples_per_second":
|
198 |
-
"eval_steps_per_second":
|
199 |
"step": 1220
|
200 |
},
|
201 |
{
|
202 |
"epoch": 11.0,
|
203 |
-
"grad_norm":
|
204 |
"learning_rate": 2.25e-05,
|
205 |
-
"loss": 0.
|
206 |
"step": 1342
|
207 |
},
|
208 |
{
|
209 |
"epoch": 11.0,
|
210 |
-
"eval_accuracy": 0.
|
211 |
-
"eval_f1": 0.
|
212 |
-
"eval_loss": 0.
|
213 |
-
"eval_precision": 0.
|
214 |
-
"eval_recall": 0.
|
215 |
-
"eval_runtime":
|
216 |
-
"eval_samples_per_second":
|
217 |
-
"eval_steps_per_second":
|
218 |
"step": 1342
|
219 |
},
|
220 |
{
|
221 |
"epoch": 12.0,
|
222 |
-
"grad_norm": 8.
|
223 |
"learning_rate": 2e-05,
|
224 |
-
"loss": 0.
|
225 |
"step": 1464
|
226 |
},
|
227 |
{
|
228 |
"epoch": 12.0,
|
229 |
-
"eval_accuracy": 0.
|
230 |
-
"eval_f1": 0.
|
231 |
-
"eval_loss": 0.
|
232 |
-
"eval_precision": 0.
|
233 |
-
"eval_recall": 0.
|
234 |
-
"eval_runtime":
|
235 |
-
"eval_samples_per_second":
|
236 |
-
"eval_steps_per_second":
|
237 |
"step": 1464
|
238 |
},
|
239 |
{
|
240 |
"epoch": 13.0,
|
241 |
-
"grad_norm":
|
242 |
"learning_rate": 1.75e-05,
|
243 |
-
"loss": 0.
|
244 |
"step": 1586
|
245 |
},
|
246 |
{
|
247 |
"epoch": 13.0,
|
248 |
-
"eval_accuracy": 0.
|
249 |
-
"eval_f1": 0.
|
250 |
-
"eval_loss": 0.
|
251 |
-
"eval_precision": 0.
|
252 |
-
"eval_recall": 0.
|
253 |
-
"eval_runtime":
|
254 |
-
"eval_samples_per_second":
|
255 |
-
"eval_steps_per_second":
|
256 |
"step": 1586
|
257 |
},
|
258 |
{
|
259 |
"epoch": 14.0,
|
260 |
-
"grad_norm":
|
261 |
"learning_rate": 1.5e-05,
|
262 |
-
"loss": 0.
|
263 |
"step": 1708
|
264 |
},
|
265 |
{
|
266 |
"epoch": 14.0,
|
267 |
-
"eval_accuracy": 0.
|
268 |
-
"eval_f1": 0.
|
269 |
-
"eval_loss": 0.
|
270 |
-
"eval_precision": 0.
|
271 |
-
"eval_recall": 0.
|
272 |
-
"eval_runtime":
|
273 |
-
"eval_samples_per_second":
|
274 |
-
"eval_steps_per_second":
|
275 |
"step": 1708
|
276 |
},
|
277 |
{
|
278 |
"epoch": 15.0,
|
279 |
-
"grad_norm":
|
280 |
"learning_rate": 1.25e-05,
|
281 |
-
"loss": 0.
|
282 |
"step": 1830
|
283 |
},
|
284 |
{
|
285 |
"epoch": 15.0,
|
286 |
-
"eval_accuracy": 0.
|
287 |
-
"eval_f1": 0.
|
288 |
-
"eval_loss": 0.
|
289 |
-
"eval_precision": 0.
|
290 |
-
"eval_recall": 0.
|
291 |
-
"eval_runtime":
|
292 |
-
"eval_samples_per_second":
|
293 |
-
"eval_steps_per_second":
|
294 |
"step": 1830
|
295 |
},
|
296 |
{
|
297 |
"epoch": 16.0,
|
298 |
-
"grad_norm":
|
299 |
"learning_rate": 1e-05,
|
300 |
-
"loss": 0.
|
301 |
"step": 1952
|
302 |
},
|
303 |
{
|
304 |
"epoch": 16.0,
|
305 |
-
"eval_accuracy": 0.
|
306 |
-
"eval_f1": 0.
|
307 |
-
"eval_loss": 0.
|
308 |
-
"eval_precision": 0.
|
309 |
-
"eval_recall": 0.
|
310 |
-
"eval_runtime":
|
311 |
-
"eval_samples_per_second":
|
312 |
-
"eval_steps_per_second":
|
313 |
"step": 1952
|
314 |
},
|
315 |
{
|
316 |
"epoch": 17.0,
|
317 |
-
"grad_norm":
|
318 |
"learning_rate": 7.5e-06,
|
319 |
-
"loss": 0.
|
320 |
"step": 2074
|
321 |
},
|
322 |
{
|
323 |
"epoch": 17.0,
|
324 |
-
"eval_accuracy": 0.
|
325 |
-
"eval_f1": 0.
|
326 |
-
"eval_loss": 0.
|
327 |
-
"eval_precision": 0.
|
328 |
-
"eval_recall": 0.
|
329 |
-
"eval_runtime":
|
330 |
-
"eval_samples_per_second":
|
331 |
-
"eval_steps_per_second":
|
332 |
"step": 2074
|
333 |
},
|
334 |
{
|
335 |
"epoch": 18.0,
|
336 |
-
"grad_norm": 1.
|
337 |
"learning_rate": 5e-06,
|
338 |
-
"loss": 0.
|
339 |
"step": 2196
|
340 |
},
|
341 |
{
|
342 |
"epoch": 18.0,
|
343 |
-
"eval_accuracy": 0.
|
344 |
-
"eval_f1": 0.
|
345 |
-
"eval_loss": 0.
|
346 |
-
"eval_precision": 0.
|
347 |
-
"eval_recall": 0.
|
348 |
-
"eval_runtime":
|
349 |
-
"eval_samples_per_second":
|
350 |
-
"eval_steps_per_second":
|
351 |
"step": 2196
|
352 |
},
|
353 |
{
|
354 |
"epoch": 19.0,
|
355 |
-
"grad_norm":
|
356 |
"learning_rate": 2.5e-06,
|
357 |
-
"loss": 0.
|
358 |
"step": 2318
|
359 |
},
|
360 |
{
|
361 |
"epoch": 19.0,
|
362 |
-
"eval_accuracy": 0.
|
363 |
-
"eval_f1": 0.
|
364 |
-
"eval_loss": 0.
|
365 |
-
"eval_precision": 0.
|
366 |
-
"eval_recall": 0.
|
367 |
-
"eval_runtime":
|
368 |
-
"eval_samples_per_second":
|
369 |
-
"eval_steps_per_second":
|
370 |
"step": 2318
|
371 |
},
|
372 |
{
|
373 |
"epoch": 20.0,
|
374 |
-
"grad_norm":
|
375 |
"learning_rate": 0.0,
|
376 |
-
"loss": 0.
|
377 |
"step": 2440
|
378 |
},
|
379 |
{
|
380 |
"epoch": 20.0,
|
381 |
-
"eval_accuracy": 0.
|
382 |
-
"eval_f1": 0.
|
383 |
-
"eval_loss": 0.
|
384 |
-
"eval_precision": 0.
|
385 |
-
"eval_recall": 0.
|
386 |
-
"eval_runtime":
|
387 |
-
"eval_samples_per_second":
|
388 |
-
"eval_steps_per_second":
|
389 |
"step": 2440
|
390 |
},
|
391 |
{
|
392 |
"epoch": 20.0,
|
393 |
"step": 2440,
|
394 |
"total_flos": 8444128359504000.0,
|
395 |
-
"train_loss": 0.
|
396 |
-
"train_runtime":
|
397 |
-
"train_samples_per_second":
|
398 |
-
"train_steps_per_second":
|
399 |
}
|
400 |
],
|
401 |
"logging_steps": 500,
|
|
|
10 |
"log_history": [
|
11 |
{
|
12 |
"epoch": 1.0,
|
13 |
+
"grad_norm": 5.112319469451904,
|
14 |
"learning_rate": 4.75e-05,
|
15 |
+
"loss": 0.5509,
|
16 |
"step": 122
|
17 |
},
|
18 |
{
|
19 |
"epoch": 1.0,
|
20 |
+
"eval_accuracy": 0.7393483709273183,
|
21 |
+
"eval_f1": 0.6507070707070707,
|
22 |
+
"eval_loss": 0.4983255863189697,
|
23 |
+
"eval_precision": 0.6800605637083625,
|
24 |
+
"eval_recall": 0.6405710129114385,
|
25 |
+
"eval_runtime": 1.7657,
|
26 |
+
"eval_samples_per_second": 225.971,
|
27 |
+
"eval_steps_per_second": 28.317,
|
28 |
"step": 122
|
29 |
},
|
30 |
{
|
31 |
"epoch": 2.0,
|
32 |
+
"grad_norm": 3.6866044998168945,
|
33 |
"learning_rate": 4.5e-05,
|
34 |
+
"loss": 0.4511,
|
35 |
"step": 244
|
36 |
},
|
37 |
{
|
38 |
"epoch": 2.0,
|
39 |
+
"eval_accuracy": 0.7769423558897243,
|
40 |
+
"eval_f1": 0.7593078346448687,
|
41 |
+
"eval_loss": 0.4377373456954956,
|
42 |
+
"eval_precision": 0.7546743295019157,
|
43 |
+
"eval_recall": 0.8021913075104565,
|
44 |
+
"eval_runtime": 1.769,
|
45 |
+
"eval_samples_per_second": 225.555,
|
46 |
+
"eval_steps_per_second": 28.265,
|
47 |
"step": 244
|
48 |
},
|
49 |
{
|
50 |
"epoch": 3.0,
|
51 |
+
"grad_norm": 3.584764242172241,
|
52 |
"learning_rate": 4.25e-05,
|
53 |
+
"loss": 0.368,
|
54 |
"step": 366
|
55 |
},
|
56 |
{
|
57 |
"epoch": 3.0,
|
58 |
+
"eval_accuracy": 0.8571428571428571,
|
59 |
+
"eval_f1": 0.8196102381877741,
|
60 |
+
"eval_loss": 0.32603567838668823,
|
61 |
+
"eval_precision": 0.8381270903010034,
|
62 |
+
"eval_recall": 0.8064193489725404,
|
63 |
+
"eval_runtime": 1.7715,
|
64 |
+
"eval_samples_per_second": 225.23,
|
65 |
+
"eval_steps_per_second": 28.224,
|
66 |
"step": 366
|
67 |
},
|
68 |
{
|
69 |
"epoch": 4.0,
|
70 |
+
"grad_norm": 2.8483095169067383,
|
71 |
"learning_rate": 4e-05,
|
72 |
+
"loss": 0.3019,
|
73 |
"step": 488
|
74 |
},
|
75 |
{
|
76 |
"epoch": 4.0,
|
77 |
+
"eval_accuracy": 0.8646616541353384,
|
78 |
+
"eval_f1": 0.8333281762485303,
|
79 |
+
"eval_loss": 0.30364951491355896,
|
80 |
+
"eval_precision": 0.8410471369819678,
|
81 |
+
"eval_recall": 0.8267412256773959,
|
82 |
+
"eval_runtime": 1.7702,
|
83 |
+
"eval_samples_per_second": 225.393,
|
84 |
+
"eval_steps_per_second": 28.245,
|
85 |
"step": 488
|
86 |
},
|
87 |
{
|
88 |
"epoch": 5.0,
|
89 |
+
"grad_norm": 2.774143934249878,
|
90 |
"learning_rate": 3.7500000000000003e-05,
|
91 |
+
"loss": 0.2668,
|
92 |
"step": 610
|
93 |
},
|
94 |
{
|
95 |
"epoch": 5.0,
|
96 |
+
"eval_accuracy": 0.8671679197994987,
|
97 |
+
"eval_f1": 0.8424651921601347,
|
98 |
+
"eval_loss": 0.31921207904815674,
|
99 |
+
"eval_precision": 0.8372140762463343,
|
100 |
+
"eval_recall": 0.8485179123476996,
|
101 |
+
"eval_runtime": 1.7714,
|
102 |
+
"eval_samples_per_second": 225.248,
|
103 |
+
"eval_steps_per_second": 28.227,
|
104 |
"step": 610
|
105 |
},
|
106 |
{
|
107 |
"epoch": 6.0,
|
108 |
+
"grad_norm": 4.2327117919921875,
|
109 |
"learning_rate": 3.5e-05,
|
110 |
+
"loss": 0.2471,
|
111 |
"step": 732
|
112 |
},
|
113 |
{
|
114 |
"epoch": 6.0,
|
115 |
+
"eval_accuracy": 0.8621553884711779,
|
116 |
+
"eval_f1": 0.8380263497804185,
|
117 |
+
"eval_loss": 0.30589351058006287,
|
118 |
+
"eval_precision": 0.830503344095941,
|
119 |
+
"eval_recall": 0.8474722676850337,
|
120 |
+
"eval_runtime": 1.7732,
|
121 |
+
"eval_samples_per_second": 225.015,
|
122 |
+
"eval_steps_per_second": 28.197,
|
123 |
"step": 732
|
124 |
},
|
125 |
{
|
126 |
"epoch": 7.0,
|
127 |
+
"grad_norm": 0.5115749835968018,
|
128 |
"learning_rate": 3.2500000000000004e-05,
|
129 |
+
"loss": 0.2422,
|
130 |
"step": 854
|
131 |
},
|
132 |
{
|
133 |
"epoch": 7.0,
|
134 |
+
"eval_accuracy": 0.87468671679198,
|
135 |
+
"eval_f1": 0.8524146298159436,
|
136 |
+
"eval_loss": 0.2949831783771515,
|
137 |
+
"eval_precision": 0.8451250578971746,
|
138 |
+
"eval_recall": 0.8613384251682124,
|
139 |
+
"eval_runtime": 1.7731,
|
140 |
+
"eval_samples_per_second": 225.024,
|
141 |
+
"eval_steps_per_second": 28.198,
|
142 |
"step": 854
|
143 |
},
|
144 |
{
|
145 |
"epoch": 8.0,
|
146 |
+
"grad_norm": 1.2918312549591064,
|
147 |
"learning_rate": 3e-05,
|
148 |
+
"loss": 0.2258,
|
149 |
"step": 976
|
150 |
},
|
151 |
{
|
152 |
"epoch": 8.0,
|
153 |
+
"eval_accuracy": 0.8721804511278195,
|
154 |
+
"eval_f1": 0.8454251965513313,
|
155 |
+
"eval_loss": 0.29280924797058105,
|
156 |
+
"eval_precision": 0.8463049835506276,
|
157 |
+
"eval_recall": 0.8445626477541371,
|
158 |
+
"eval_runtime": 1.7799,
|
159 |
+
"eval_samples_per_second": 224.171,
|
160 |
+
"eval_steps_per_second": 28.092,
|
161 |
"step": 976
|
162 |
},
|
163 |
{
|
164 |
"epoch": 9.0,
|
165 |
+
"grad_norm": 5.160737037658691,
|
166 |
"learning_rate": 2.7500000000000004e-05,
|
167 |
+
"loss": 0.2054,
|
168 |
"step": 1098
|
169 |
},
|
170 |
{
|
171 |
"epoch": 9.0,
|
172 |
+
"eval_accuracy": 0.8796992481203008,
|
173 |
+
"eval_f1": 0.8533986527862829,
|
174 |
+
"eval_loss": 0.30492648482322693,
|
175 |
+
"eval_precision": 0.8572003218020917,
|
176 |
+
"eval_recall": 0.8498817966903074,
|
177 |
+
"eval_runtime": 1.779,
|
178 |
+
"eval_samples_per_second": 224.288,
|
179 |
+
"eval_steps_per_second": 28.106,
|
180 |
"step": 1098
|
181 |
},
|
182 |
{
|
183 |
"epoch": 10.0,
|
184 |
+
"grad_norm": 3.917464017868042,
|
185 |
"learning_rate": 2.5e-05,
|
186 |
+
"loss": 0.2009,
|
187 |
"step": 1220
|
188 |
},
|
189 |
{
|
190 |
"epoch": 10.0,
|
191 |
+
"eval_accuracy": 0.87468671679198,
|
192 |
+
"eval_f1": 0.8488361520276414,
|
193 |
+
"eval_loss": 0.30127042531967163,
|
194 |
+
"eval_precision": 0.8488361520276414,
|
195 |
+
"eval_recall": 0.8488361520276414,
|
196 |
+
"eval_runtime": 1.7757,
|
197 |
+
"eval_samples_per_second": 224.7,
|
198 |
+
"eval_steps_per_second": 28.158,
|
199 |
"step": 1220
|
200 |
},
|
201 |
{
|
202 |
"epoch": 11.0,
|
203 |
+
"grad_norm": 6.667805194854736,
|
204 |
"learning_rate": 2.25e-05,
|
205 |
+
"loss": 0.1755,
|
206 |
"step": 1342
|
207 |
},
|
208 |
{
|
209 |
"epoch": 11.0,
|
210 |
+
"eval_accuracy": 0.8822055137844611,
|
211 |
+
"eval_f1": 0.858259325044405,
|
212 |
+
"eval_loss": 0.30701279640197754,
|
213 |
+
"eval_precision": 0.8573798178418481,
|
214 |
+
"eval_recall": 0.8591562102200401,
|
215 |
+
"eval_runtime": 1.7942,
|
216 |
+
"eval_samples_per_second": 222.38,
|
217 |
+
"eval_steps_per_second": 27.867,
|
218 |
"step": 1342
|
219 |
},
|
220 |
{
|
221 |
"epoch": 12.0,
|
222 |
+
"grad_norm": 8.611730575561523,
|
223 |
"learning_rate": 2e-05,
|
224 |
+
"loss": 0.1821,
|
225 |
"step": 1464
|
226 |
},
|
227 |
{
|
228 |
"epoch": 12.0,
|
229 |
+
"eval_accuracy": 0.8822055137844611,
|
230 |
+
"eval_f1": 0.8568221901555235,
|
231 |
+
"eval_loss": 0.2995355427265167,
|
232 |
+
"eval_precision": 0.8596491228070176,
|
233 |
+
"eval_recall": 0.8541553009638116,
|
234 |
+
"eval_runtime": 1.7796,
|
235 |
+
"eval_samples_per_second": 224.202,
|
236 |
+
"eval_steps_per_second": 28.095,
|
237 |
"step": 1464
|
238 |
},
|
239 |
{
|
240 |
"epoch": 13.0,
|
241 |
+
"grad_norm": 2.71295428276062,
|
242 |
"learning_rate": 1.75e-05,
|
243 |
+
"loss": 0.1652,
|
244 |
"step": 1586
|
245 |
},
|
246 |
{
|
247 |
"epoch": 13.0,
|
248 |
+
"eval_accuracy": 0.8847117794486216,
|
249 |
+
"eval_f1": 0.866029197080292,
|
250 |
+
"eval_loss": 0.3272043764591217,
|
251 |
+
"eval_precision": 0.8552631578947368,
|
252 |
+
"eval_recall": 0.8809328968903437,
|
253 |
+
"eval_runtime": 1.7775,
|
254 |
+
"eval_samples_per_second": 224.467,
|
255 |
+
"eval_steps_per_second": 28.129,
|
256 |
"step": 1586
|
257 |
},
|
258 |
{
|
259 |
"epoch": 14.0,
|
260 |
+
"grad_norm": 5.373868942260742,
|
261 |
"learning_rate": 1.5e-05,
|
262 |
+
"loss": 0.1566,
|
263 |
"step": 1708
|
264 |
},
|
265 |
{
|
266 |
"epoch": 14.0,
|
267 |
+
"eval_accuracy": 0.8897243107769424,
|
268 |
+
"eval_f1": 0.8718540145985401,
|
269 |
+
"eval_loss": 0.33357149362564087,
|
270 |
+
"eval_precision": 0.8609022556390977,
|
271 |
+
"eval_recall": 0.886979450809238,
|
272 |
+
"eval_runtime": 1.7836,
|
273 |
+
"eval_samples_per_second": 223.703,
|
274 |
+
"eval_steps_per_second": 28.033,
|
275 |
"step": 1708
|
276 |
},
|
277 |
{
|
278 |
"epoch": 15.0,
|
279 |
+
"grad_norm": 5.369639873504639,
|
280 |
"learning_rate": 1.25e-05,
|
281 |
+
"loss": 0.1634,
|
282 |
"step": 1830
|
283 |
},
|
284 |
{
|
285 |
"epoch": 15.0,
|
286 |
+
"eval_accuracy": 0.8847117794486216,
|
287 |
+
"eval_f1": 0.8622899159663866,
|
288 |
+
"eval_loss": 0.314995676279068,
|
289 |
+
"eval_precision": 0.8589244307033712,
|
290 |
+
"eval_recall": 0.8659301691216585,
|
291 |
+
"eval_runtime": 1.777,
|
292 |
+
"eval_samples_per_second": 224.539,
|
293 |
+
"eval_steps_per_second": 28.138,
|
294 |
"step": 1830
|
295 |
},
|
296 |
{
|
297 |
"epoch": 16.0,
|
298 |
+
"grad_norm": 6.779192924499512,
|
299 |
"learning_rate": 1e-05,
|
300 |
+
"loss": 0.1496,
|
301 |
"step": 1952
|
302 |
},
|
303 |
{
|
304 |
"epoch": 16.0,
|
305 |
+
"eval_accuracy": 0.8922305764411027,
|
306 |
+
"eval_f1": 0.8696722245432793,
|
307 |
+
"eval_loss": 0.3320792317390442,
|
308 |
+
"eval_precision": 0.8706135006701596,
|
309 |
+
"eval_recall": 0.8687488634297145,
|
310 |
+
"eval_runtime": 1.7833,
|
311 |
+
"eval_samples_per_second": 223.741,
|
312 |
+
"eval_steps_per_second": 28.038,
|
313 |
"step": 1952
|
314 |
},
|
315 |
{
|
316 |
"epoch": 17.0,
|
317 |
+
"grad_norm": 1.1515932083129883,
|
318 |
"learning_rate": 7.5e-06,
|
319 |
+
"loss": 0.1355,
|
320 |
"step": 2074
|
321 |
},
|
322 |
{
|
323 |
"epoch": 17.0,
|
324 |
+
"eval_accuracy": 0.8847117794486216,
|
325 |
+
"eval_f1": 0.8616171059774413,
|
326 |
+
"eval_loss": 0.32759982347488403,
|
327 |
+
"eval_precision": 0.859873949579832,
|
328 |
+
"eval_recall": 0.8634297144935443,
|
329 |
+
"eval_runtime": 1.7782,
|
330 |
+
"eval_samples_per_second": 224.387,
|
331 |
+
"eval_steps_per_second": 28.119,
|
332 |
"step": 2074
|
333 |
},
|
334 |
{
|
335 |
"epoch": 18.0,
|
336 |
+
"grad_norm": 1.6571087837219238,
|
337 |
"learning_rate": 5e-06,
|
338 |
+
"loss": 0.1477,
|
339 |
"step": 2196
|
340 |
},
|
341 |
{
|
342 |
"epoch": 18.0,
|
343 |
+
"eval_accuracy": 0.8796992481203008,
|
344 |
+
"eval_f1": 0.8563025210084034,
|
345 |
+
"eval_loss": 0.33653610944747925,
|
346 |
+
"eval_precision": 0.8529936381473334,
|
347 |
+
"eval_recall": 0.8598836152027641,
|
348 |
+
"eval_runtime": 1.7851,
|
349 |
+
"eval_samples_per_second": 223.518,
|
350 |
+
"eval_steps_per_second": 28.01,
|
351 |
"step": 2196
|
352 |
},
|
353 |
{
|
354 |
"epoch": 19.0,
|
355 |
+
"grad_norm": 2.6701011657714844,
|
356 |
"learning_rate": 2.5e-06,
|
357 |
+
"loss": 0.1317,
|
358 |
"step": 2318
|
359 |
},
|
360 |
{
|
361 |
"epoch": 19.0,
|
362 |
+
"eval_accuracy": 0.8822055137844611,
|
363 |
+
"eval_f1": 0.858259325044405,
|
364 |
+
"eval_loss": 0.3385031819343567,
|
365 |
+
"eval_precision": 0.8573798178418481,
|
366 |
+
"eval_recall": 0.8591562102200401,
|
367 |
+
"eval_runtime": 1.7765,
|
368 |
+
"eval_samples_per_second": 224.597,
|
369 |
+
"eval_steps_per_second": 28.145,
|
370 |
"step": 2318
|
371 |
},
|
372 |
{
|
373 |
"epoch": 20.0,
|
374 |
+
"grad_norm": 3.197312593460083,
|
375 |
"learning_rate": 0.0,
|
376 |
+
"loss": 0.1267,
|
377 |
"step": 2440
|
378 |
},
|
379 |
{
|
380 |
"epoch": 20.0,
|
381 |
+
"eval_accuracy": 0.8822055137844611,
|
382 |
+
"eval_f1": 0.858259325044405,
|
383 |
+
"eval_loss": 0.3389217257499695,
|
384 |
+
"eval_precision": 0.8573798178418481,
|
385 |
+
"eval_recall": 0.8591562102200401,
|
386 |
+
"eval_runtime": 1.7779,
|
387 |
+
"eval_samples_per_second": 224.423,
|
388 |
+
"eval_steps_per_second": 28.123,
|
389 |
"step": 2440
|
390 |
},
|
391 |
{
|
392 |
"epoch": 20.0,
|
393 |
"step": 2440,
|
394 |
"total_flos": 8444128359504000.0,
|
395 |
+
"train_loss": 0.22970127551282038,
|
396 |
+
"train_runtime": 621.3103,
|
397 |
+
"train_samples_per_second": 117.107,
|
398 |
+
"train_steps_per_second": 3.927
|
399 |
}
|
400 |
],
|
401 |
"logging_steps": 500,
|