generated_from_trainer

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20230830000403

This model is a fine-tuned version of bert-large-cased on the super_glue dataset. It achieves the following results on the evaluation set:

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 35 0.5799 0.5865
No log 2.0 70 0.9689 0.4038
No log 3.0 105 0.9731 0.5865
No log 4.0 140 0.6271 0.4135
No log 5.0 175 0.3585 0.5288
No log 6.0 210 0.5032 0.6346
No log 7.0 245 0.4789 0.3654
No log 8.0 280 0.3592 0.6346
No log 9.0 315 0.6083 0.3942
No log 10.0 350 1.5261 0.3654
No log 11.0 385 0.3449 0.5962
No log 12.0 420 0.3393 0.6442
No log 13.0 455 0.6406 0.375
No log 14.0 490 0.3776 0.6346
0.7019 15.0 525 0.3404 0.6346
0.7019 16.0 560 0.3370 0.5769
0.7019 17.0 595 0.5190 0.3846
0.7019 18.0 630 0.3413 0.5385
0.7019 19.0 665 0.3289 0.6346
0.7019 20.0 700 0.3325 0.5962
0.7019 21.0 735 0.4720 0.6346
0.7019 22.0 770 0.3307 0.6442
0.7019 23.0 805 0.3899 0.6346
0.7019 24.0 840 0.4349 0.6346
0.7019 25.0 875 0.6318 0.3654
0.7019 26.0 910 0.3984 0.4327
0.7019 27.0 945 0.4749 0.6346
0.7019 28.0 980 0.5154 0.3942
0.4539 29.0 1015 0.4364 0.3654
0.4539 30.0 1050 0.3795 0.4327
0.4539 31.0 1085 0.3639 0.3942
0.4539 32.0 1120 0.5953 0.3942
0.4539 33.0 1155 0.3571 0.4712
0.4539 34.0 1190 0.3439 0.5481
0.4539 35.0 1225 0.3359 0.5769
0.4539 36.0 1260 0.4823 0.3942
0.4539 37.0 1295 0.3336 0.625
0.4539 38.0 1330 0.3474 0.4808
0.4539 39.0 1365 0.3355 0.6346
0.4539 40.0 1400 0.3357 0.6154
0.4539 41.0 1435 0.3705 0.4423
0.4539 42.0 1470 0.3329 0.5769
0.4412 43.0 1505 0.3592 0.4423
0.4412 44.0 1540 0.3311 0.6346
0.4412 45.0 1575 0.3307 0.6346
0.4412 46.0 1610 0.5444 0.6346
0.4412 47.0 1645 0.4086 0.4038
0.4412 48.0 1680 0.3420 0.6346
0.4412 49.0 1715 0.3337 0.6346
0.4412 50.0 1750 0.3533 0.5096
0.4412 51.0 1785 0.4502 0.4135
0.4412 52.0 1820 0.3679 0.4423
0.4412 53.0 1855 0.3496 0.4904
0.4412 54.0 1890 0.3580 0.4712
0.4412 55.0 1925 0.3458 0.5
0.4412 56.0 1960 0.3383 0.5865
0.4412 57.0 1995 0.3508 0.4615
0.4041 58.0 2030 0.3467 0.6346
0.4041 59.0 2065 0.3335 0.6346
0.4041 60.0 2100 0.3664 0.6346
0.4041 61.0 2135 0.4058 0.6346
0.4041 62.0 2170 0.3287 0.6346
0.4041 63.0 2205 0.3370 0.6346
0.4041 64.0 2240 0.3384 0.5865
0.4041 65.0 2275 0.3351 0.6346
0.4041 66.0 2310 0.3307 0.6538
0.4041 67.0 2345 0.3395 0.5673
0.4041 68.0 2380 0.3304 0.6538
0.4041 69.0 2415 0.3372 0.6635
0.4041 70.0 2450 0.3317 0.6346
0.4041 71.0 2485 0.3388 0.6346
0.3722 72.0 2520 0.3333 0.6346
0.3722 73.0 2555 0.3595 0.4423
0.3722 74.0 2590 0.3455 0.5
0.3722 75.0 2625 0.3298 0.6538
0.3722 76.0 2660 0.3293 0.6346
0.3722 77.0 2695 0.3927 0.4135
0.3722 78.0 2730 0.3371 0.5769
0.3722 79.0 2765 0.3306 0.6538
0.3722 80.0 2800 0.3312 0.6346

Framework versions