generated_from_trainer

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metal-graphcodebert-base-gpt4-v3

This model is a fine-tuned version of on the None 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 Text Start Acc Text End Acc Code Start Acc Code End Acc
6.085 0.03 500 6.4250 0.2513 0.2552 0.2493 0.2546 0.2460
4.3622 0.06 1000 6.4845 0.3826 0.3785 0.3578 0.4048 0.3895
3.7195 0.09 1500 6.3109 0.5014 0.4932 0.4570 0.5354 0.5199
3.4122 0.12 2000 6.0049 0.5719 0.5785 0.5381 0.5946 0.5763
3.1662 0.14 2500 6.0516 0.6142 0.6105 0.5854 0.6360 0.6249
3.0729 0.17 3000 5.7291 0.6480 0.6531 0.6173 0.6656 0.6561
2.9675 0.2 3500 5.9223 0.6478 0.6585 0.6239 0.6648 0.6438
2.94 0.23 4000 5.8322 0.6637 0.6746 0.6406 0.6768 0.6626
2.8936 0.26 4500 5.7799 0.6876 0.7013 0.6716 0.6932 0.6845
2.8697 0.29 5000 5.9136 0.6805 0.6763 0.6709 0.6880 0.6867
2.793 0.32 5500 5.6892 0.7055 0.7164 0.6785 0.7248 0.7022
2.7748 0.35 6000 5.6964 0.7079 0.7125 0.7034 0.7091 0.7067
2.7162 0.37 6500 5.8504 0.6985 0.7119 0.6784 0.6999 0.7038
2.7423 0.4 7000 5.7123 0.7191 0.7175 0.6877 0.7308 0.7405
2.6836 0.43 7500 5.6872 0.7212 0.7350 0.7081 0.7225 0.7192
2.6458 0.46 8000 5.7051 0.7233 0.7309 0.7210 0.7282 0.7133
2.6587 0.49 8500 5.8715 0.7060 0.7033 0.6877 0.7148 0.7180
2.6031 0.52 9000 5.7375 0.7331 0.7326 0.7168 0.7446 0.7384
2.5892 0.55 9500 5.6550 0.7420 0.7468 0.7282 0.7501 0.7429
2.5568 0.58 10000 5.8174 0.7191 0.7148 0.7023 0.7360 0.7232
2.5495 0.61 10500 5.8085 0.7237 0.7212 0.6921 0.7399 0.7416
2.5374 0.63 11000 5.6530 0.7377 0.7303 0.7029 0.7601 0.7573
2.5235 0.66 11500 5.7847 0.7222 0.7128 0.7158 0.7310 0.7295
2.5166 0.69 12000 5.5209 0.7452 0.7507 0.7353 0.7577 0.7370
2.4729 0.72 12500 5.7236 0.7329 0.7276 0.7171 0.7460 0.7407
2.4768 0.75 13000 5.7680 0.7371 0.7299 0.7159 0.7580 0.7444
2.4863 0.78 13500 5.7128 0.7493 0.7442 0.7307 0.7620 0.7601
2.4682 0.81 14000 5.6488 0.7547 0.7545 0.7435 0.7601 0.7608
2.4352 0.84 14500 5.6568 0.7510 0.7507 0.7446 0.7593 0.7494
2.4305 0.87 15000 5.6023 0.7550 0.7582 0.7452 0.7671 0.7495
2.4462 0.89 15500 5.6579 0.7510 0.7472 0.7296 0.7616 0.7656
2.4126 0.92 16000 5.5977 0.7625 0.7561 0.7418 0.7785 0.7738
2.4365 0.95 16500 5.5893 0.7624 0.7525 0.7401 0.7805 0.7767
2.4131 0.98 17000 5.5119 0.7767 0.7693 0.7632 0.7912 0.7832
2.3171 1.01 17500 5.6282 0.7658 0.7550 0.7540 0.7891 0.7654
2.3331 1.04 18000 5.6226 0.7603 0.7581 0.7504 0.7611 0.7718
2.3776 1.07 18500 5.7404 0.7460 0.7265 0.7182 0.7671 0.7722
2.3775 1.1 19000 5.4884 0.7724 0.7650 0.7613 0.7818 0.7816
2.3436 1.12 19500 5.6141 0.7539 0.7540 0.7324 0.7622 0.7671
2.3222 1.15 20000 5.6792 0.7586 0.7578 0.7326 0.7698 0.7742
2.3382 1.18 20500 5.6713 0.7604 0.7462 0.7436 0.7791 0.7729
2.3127 1.21 21000 5.5783 0.7748 0.7729 0.7712 0.7787 0.7763
2.3698 1.24 21500 5.4640 0.7786 0.7854 0.7711 0.7768 0.7812
2.303 1.27 22000 5.5976 0.7595 0.7513 0.7473 0.7654 0.7741
2.2949 1.3 22500 5.6816 0.7531 0.7394 0.7186 0.7745 0.7798
2.3185 1.33 23000 5.5256 0.7781 0.7767 0.7530 0.7923 0.7905
2.2885 1.36 23500 5.5717 0.7599 0.7509 0.7470 0.7725 0.7693
2.3125 1.38 24000 5.5428 0.7674 0.7624 0.7460 0.7814 0.7798
2.2726 1.41 24500 5.5754 0.7622 0.7767 0.7408 0.7660 0.7653
2.3074 1.44 25000 5.4123 0.7848 0.7901 0.7803 0.7849 0.7840
2.275 1.47 25500 5.5832 0.7614 0.7577 0.7373 0.7808 0.7697
2.2766 1.5 26000 5.5349 0.7668 0.7616 0.7377 0.7812 0.7869
2.2911 1.53 26500 5.5479 0.7600 0.7588 0.7389 0.7759 0.7664
2.2968 1.56 27000 5.6977 0.7486 0.7354 0.7203 0.7683 0.7705
2.2763 1.59 27500 5.4139 0.7824 0.7710 0.7625 0.7985 0.7977
2.296 1.61 28000 5.3677 0.7812 0.7885 0.7625 0.7942 0.7795
2.281 1.64 28500 5.4631 0.7737 0.7703 0.7652 0.7788 0.7803
2.2505 1.67 29000 5.6172 0.7621 0.7513 0.7371 0.7828 0.7773
2.2856 1.7 29500 5.5993 0.7593 0.7556 0.7342 0.7732 0.7742
2.2962 1.73 30000 5.5468 0.7655 0.7595 0.7297 0.7833 0.7896
2.2636 1.76 30500 5.5076 0.7746 0.7704 0.7534 0.7902 0.7845
2.2386 1.79 31000 5.6392 0.7611 0.7515 0.7412 0.7763 0.7755
2.2289 1.82 31500 5.6283 0.7592 0.7494 0.7372 0.7751 0.7752
2.2608 1.85 32000 5.4233 0.7842 0.7933 0.7737 0.7837 0.7860
2.2529 1.87 32500 5.4549 0.7838 0.7815 0.7622 0.7985 0.7928
2.2548 1.9 33000 5.4714 0.7806 0.7753 0.7582 0.8004 0.7886
2.2144 1.93 33500 5.4302 0.7828 0.7736 0.7605 0.8025 0.7947
2.2533 1.96 34000 5.5000 0.7739 0.7661 0.7546 0.7876 0.7875
2.2362 1.99 34500 5.5129 0.7727 0.7629 0.7494 0.7869 0.7915
2.2086 2.02 35000 5.5991 0.7624 0.7551 0.7324 0.7812 0.7812
2.2194 2.05 35500 5.4611 0.7889 0.7807 0.7638 0.8081 0.8030
2.1732 2.08 36000 5.5642 0.7674 0.7503 0.7431 0.7908 0.7854
2.1972 2.11 36500 5.4433 0.7834 0.7806 0.7618 0.7981 0.7931
2.2376 2.13 37000 5.4670 0.7775 0.7755 0.7640 0.7873 0.7833
2.1921 2.16 37500 5.4935 0.7735 0.7686 0.7525 0.7817 0.7912
2.1789 2.19 38000 5.4306 0.7831 0.7782 0.7625 0.7985 0.7933
2.1649 2.22 38500 5.3896 0.7866 0.7859 0.7676 0.7936 0.7995
2.1872 2.25 39000 5.5065 0.7766 0.7669 0.7530 0.7928 0.7937
2.1894 2.28 39500 5.3958 0.7885 0.7878 0.7720 0.7987 0.7955
2.1978 2.31 40000 5.4631 0.7788 0.7707 0.7583 0.7927 0.7933
2.1768 2.34 40500 5.3886 0.7838 0.7795 0.7592 0.8006 0.7959
2.1812 2.36 41000 5.5139 0.7712 0.7557 0.7446 0.7943 0.7903
2.1793 2.39 41500 5.5179 0.7758 0.7712 0.7577 0.7881 0.7863
2.1746 2.42 42000 5.4554 0.7798 0.7791 0.7665 0.7879 0.7857
2.1891 2.45 42500 5.4976 0.7794 0.7729 0.7539 0.7956 0.7951
2.1623 2.48 43000 5.5901 0.7645 0.7530 0.7326 0.7912 0.7812
2.1794 2.51 43500 5.5192 0.7733 0.7682 0.7416 0.7941 0.7894
2.1593 2.54 44000 5.5453 0.7709 0.7673 0.7390 0.7911 0.7862
2.1414 2.57 44500 5.5045 0.7755 0.7676 0.7471 0.7964 0.7910
2.1342 2.6 45000 5.4696 0.7795 0.7711 0.7530 0.7980 0.7959
2.1514 2.62 45500 5.5181 0.7729 0.7661 0.7377 0.7953 0.7926
2.1307 2.65 46000 5.4156 0.7850 0.7814 0.7607 0.8002 0.7979
2.173 2.68 46500 5.4603 0.7842 0.7750 0.7546 0.8043 0.8027
2.2072 2.71 47000 5.4345 0.7864 0.7793 0.7605 0.8053 0.8004
2.1851 2.74 47500 5.4575 0.7846 0.7778 0.7572 0.8062 0.7973
2.1698 2.77 48000 5.4666 0.7806 0.7772 0.7523 0.7975 0.7953
2.1684 2.8 48500 5.4788 0.7799 0.7743 0.7525 0.7992 0.7938
2.167 2.83 49000 5.4683 0.7811 0.7822 0.7571 0.7953 0.7896
2.1202 2.85 49500 5.4364 0.7859 0.7852 0.7631 0.7985 0.7970
2.1699 2.88 50000 5.4853 0.7789 0.7722 0.7460 0.8023 0.7949
2.165 2.91 50500 5.4848 0.7793 0.7759 0.7517 0.7977 0.7921
2.1757 2.94 51000 5.4779 0.7802 0.7761 0.7511 0.7992 0.7942
2.1343 2.97 51500 5.5095 0.7763 0.7697 0.7453 0.7986 0.7917
2.1312 3.0 52000 5.4895 0.7783 0.7724 0.7490 0.7993 0.7926

Framework versions