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Yolo_temp_v2

This model is just my practice..
You don't need it
It trained for soccer score detect

This model is a fine-tuned version of SmallPS/Yolo_temp on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5546
  • Map: 0.5846
  • Map 50: 0.8972
  • Map 75: 0.6382
  • Map Small: -1.0
  • Map Medium: 0.5947
  • Map Large: 0.6248
  • Mar 1: 0.6
  • Mar 10: 0.702
  • Mar 100: 0.7102
  • Mar Small: -1.0
  • Mar Medium: 0.7085
  • Mar Large: 0.75
  • Map Score: 0.5846
  • Mar 100 Score: 0.7102

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:

  • learning_rate: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 7
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 300

Training results

Training Loss Epoch Step Validation Loss Map Map 50 Map 75 Map Small Map Medium Map Large Mar 1 Mar 10 Mar 100 Mar Small Mar Medium Mar Large Map Score Mar 100 Score
No log 1.0 16 1.2696 0.1881 0.4143 0.1494 -1.0 0.1797 0.4208 0.2571 0.3714 0.4041 -1.0 0.4021 0.45 0.1881 0.4041
No log 2.0 32 1.1900 0.1981 0.4419 0.1517 -1.0 0.1923 0.3282 0.2816 0.3776 0.4061 -1.0 0.4064 0.4 0.1981 0.4061
No log 3.0 48 1.0691 0.2442 0.4764 0.2372 -1.0 0.2422 0.3282 0.3245 0.4327 0.4612 -1.0 0.4638 0.4 0.2442 0.4612
No log 4.0 64 1.0659 0.2254 0.4935 0.1714 -1.0 0.2215 0.3282 0.3041 0.4286 0.4878 -1.0 0.4915 0.4 0.2254 0.4878
No log 5.0 80 0.9351 0.2703 0.5069 0.2185 -1.0 0.2629 0.3535 0.3327 0.4571 0.5122 -1.0 0.5191 0.35 0.2703 0.5122
No log 6.0 96 1.0090 0.2442 0.5207 0.2164 -1.0 0.2475 0.2272 0.3388 0.4469 0.4592 -1.0 0.4681 0.25 0.2442 0.4592
No log 7.0 112 0.9013 0.2855 0.5446 0.2492 -1.0 0.2823 0.303 0.3939 0.5143 0.5347 -1.0 0.5447 0.3 0.2855 0.5347
No log 8.0 128 0.9098 0.3188 0.5858 0.3024 -1.0 0.3173 0.303 0.3918 0.5265 0.5327 -1.0 0.5426 0.3 0.3188 0.5327
No log 9.0 144 0.9151 0.3111 0.5946 0.3054 -1.0 0.3041 0.3535 0.3816 0.5184 0.5265 -1.0 0.534 0.35 0.3111 0.5265
No log 10.0 160 0.9227 0.2928 0.6048 0.1544 -1.0 0.2847 0.404 0.349 0.5286 0.5735 -1.0 0.5809 0.4 0.2928 0.5735
No log 11.0 176 0.8485 0.3413 0.643 0.3327 -1.0 0.3372 0.3535 0.3857 0.5531 0.5816 -1.0 0.5915 0.35 0.3413 0.5816
No log 12.0 192 0.8130 0.3743 0.6853 0.351 -1.0 0.3766 0.3408 0.4327 0.5673 0.6041 -1.0 0.6128 0.4 0.3743 0.6041
No log 13.0 208 0.8337 0.3572 0.6654 0.279 -1.0 0.3594 0.303 0.3776 0.549 0.5653 -1.0 0.5766 0.3 0.3572 0.5653
No log 14.0 224 0.8131 0.3727 0.7121 0.3664 -1.0 0.3687 0.404 0.398 0.5673 0.5755 -1.0 0.583 0.4 0.3727 0.5755
No log 15.0 240 0.8091 0.3846 0.7159 0.3639 -1.0 0.3821 0.404 0.4204 0.5367 0.5429 -1.0 0.5489 0.4 0.3846 0.5429
No log 16.0 256 0.8173 0.3607 0.6692 0.3201 -1.0 0.3619 0.303 0.4286 0.5163 0.5184 -1.0 0.5277 0.3 0.3607 0.5184
No log 17.0 272 0.7498 0.3988 0.7452 0.39 -1.0 0.399 0.404 0.4429 0.5633 0.5898 -1.0 0.5979 0.4 0.3988 0.5898
No log 18.0 288 0.7925 0.3469 0.7448 0.2244 -1.0 0.3466 0.3535 0.3776 0.551 0.5735 -1.0 0.583 0.35 0.3469 0.5735
No log 19.0 304 0.7415 0.381 0.693 0.3322 -1.0 0.38 0.404 0.4388 0.6306 0.6429 -1.0 0.6532 0.4 0.381 0.6429
No log 20.0 320 0.7889 0.3667 0.6554 0.3608 -1.0 0.364 0.404 0.4143 0.598 0.6082 -1.0 0.617 0.4 0.3667 0.6082
No log 21.0 336 0.8231 0.3432 0.7116 0.2408 -1.0 0.341 0.404 0.4061 0.5878 0.6245 -1.0 0.634 0.4 0.3432 0.6245
No log 22.0 352 0.7992 0.3715 0.7235 0.2741 -1.0 0.3754 0.303 0.4531 0.5286 0.5449 -1.0 0.5553 0.3 0.3715 0.5449
No log 23.0 368 0.7316 0.4033 0.7347 0.3998 -1.0 0.4065 0.3535 0.4327 0.5673 0.5837 -1.0 0.5936 0.35 0.4033 0.5837
No log 24.0 384 0.7764 0.3641 0.7593 0.3143 -1.0 0.3648 0.303 0.3816 0.549 0.5633 -1.0 0.5745 0.3 0.3641 0.5633
No log 25.0 400 0.6661 0.4535 0.7634 0.5207 -1.0 0.4604 0.303 0.4776 0.6143 0.6163 -1.0 0.6298 0.3 0.4535 0.6163
No log 26.0 416 0.6906 0.424 0.7476 0.5043 -1.0 0.4256 0.404 0.4408 0.6184 0.6347 -1.0 0.6447 0.4 0.424 0.6347
No log 27.0 432 0.7428 0.4324 0.7994 0.3861 -1.0 0.4376 0.3093 0.4388 0.6061 0.6245 -1.0 0.6362 0.35 0.4324 0.6245
No log 28.0 448 0.7269 0.4309 0.7828 0.43 -1.0 0.4365 0.303 0.4592 0.5531 0.5592 -1.0 0.5702 0.3 0.4309 0.5592
No log 29.0 464 0.6603 0.4712 0.7707 0.5722 -1.0 0.4758 0.3535 0.498 0.598 0.602 -1.0 0.6128 0.35 0.4712 0.602
No log 30.0 480 0.6552 0.4833 0.8068 0.5106 -1.0 0.4887 0.3535 0.5408 0.6143 0.6306 -1.0 0.6426 0.35 0.4833 0.6306
No log 31.0 496 0.6957 0.457 0.7896 0.5001 -1.0 0.4614 0.3535 0.5061 0.6122 0.6347 -1.0 0.6468 0.35 0.457 0.6347
0.6799 32.0 512 0.7050 0.4462 0.7812 0.4747 -1.0 0.4467 0.404 0.4898 0.6122 0.6327 -1.0 0.6426 0.4 0.4462 0.6327
0.6799 33.0 528 0.6470 0.489 0.8033 0.5607 -1.0 0.492 0.404 0.498 0.6204 0.6429 -1.0 0.6532 0.4 0.489 0.6429
0.6799 34.0 544 0.6712 0.4849 0.8225 0.5734 -1.0 0.4899 0.3535 0.5102 0.6286 0.6449 -1.0 0.6574 0.35 0.4849 0.6449
0.6799 35.0 560 0.6389 0.4982 0.8138 0.6065 -1.0 0.5071 0.303 0.5224 0.6367 0.6571 -1.0 0.6723 0.3 0.4982 0.6571
0.6799 36.0 576 0.6874 0.4411 0.8209 0.4435 -1.0 0.4475 0.3066 0.4918 0.6102 0.6286 -1.0 0.6404 0.35 0.4411 0.6286
0.6799 37.0 592 0.6517 0.4841 0.8064 0.5304 -1.0 0.4953 0.303 0.5367 0.6163 0.6306 -1.0 0.6447 0.3 0.4841 0.6306
0.6799 38.0 608 0.7613 0.3792 0.8192 0.2273 -1.0 0.3839 0.2637 0.4265 0.5939 0.6143 -1.0 0.6255 0.35 0.3792 0.6143
0.6799 39.0 624 0.6265 0.5149 0.8449 0.4943 -1.0 0.5237 0.3535 0.5429 0.6265 0.6633 -1.0 0.6766 0.35 0.5149 0.6633
0.6799 40.0 640 0.6189 0.5142 0.7951 0.6194 -1.0 0.5212 0.3535 0.5143 0.6571 0.6755 -1.0 0.6894 0.35 0.5142 0.6755
0.6799 41.0 656 0.6452 0.4971 0.7831 0.5002 -1.0 0.509 0.303 0.5327 0.6184 0.6245 -1.0 0.6383 0.3 0.4971 0.6245
0.6799 42.0 672 0.6226 0.5068 0.8189 0.5253 -1.0 0.519 0.303 0.5429 0.649 0.6633 -1.0 0.6787 0.3 0.5068 0.6633
0.6799 43.0 688 0.7003 0.4344 0.8059 0.4218 -1.0 0.4438 0.3525 0.4694 0.6286 0.6449 -1.0 0.6574 0.35 0.4344 0.6449
0.6799 44.0 704 0.6044 0.523 0.8274 0.5429 -1.0 0.532 0.3525 0.5408 0.6469 0.6673 -1.0 0.6809 0.35 0.523 0.6673
0.6799 45.0 720 0.6762 0.4865 0.8052 0.4934 -1.0 0.4918 0.3535 0.5204 0.6143 0.6245 -1.0 0.6362 0.35 0.4865 0.6245
0.6799 46.0 736 0.6556 0.485 0.8938 0.551 -1.0 0.4922 0.3564 0.5143 0.6571 0.6714 -1.0 0.683 0.4 0.485 0.6714
0.6799 47.0 752 0.6247 0.5193 0.826 0.5423 -1.0 0.5303 0.3535 0.5531 0.6612 0.6714 -1.0 0.6851 0.35 0.5193 0.6714
0.6799 48.0 768 0.6410 0.4604 0.8627 0.466 -1.0 0.4682 0.403 0.5265 0.6265 0.6429 -1.0 0.6532 0.4 0.4604 0.6429
0.6799 49.0 784 0.6143 0.4827 0.8077 0.5629 -1.0 0.49 0.403 0.5286 0.6449 0.6551 -1.0 0.666 0.4 0.4827 0.6551
0.6799 50.0 800 0.5896 0.5047 0.861 0.5615 -1.0 0.5083 0.4525 0.5735 0.6571 0.6735 -1.0 0.683 0.45 0.5047 0.6735
0.6799 51.0 816 0.6515 0.4615 0.8986 0.3498 -1.0 0.4708 0.3083 0.5265 0.6388 0.6531 -1.0 0.6638 0.4 0.4615 0.6531
0.6799 52.0 832 0.6333 0.4879 0.8429 0.4779 -1.0 0.5003 0.3543 0.5388 0.6265 0.6388 -1.0 0.6489 0.4 0.4879 0.6388
0.6799 53.0 848 0.6802 0.4719 0.8641 0.4799 -1.0 0.4709 0.503 0.5143 0.6061 0.6122 -1.0 0.617 0.5 0.4719 0.6122
0.6799 54.0 864 0.6613 0.4744 0.8604 0.4478 -1.0 0.4776 0.4553 0.5041 0.6306 0.649 -1.0 0.6553 0.5 0.4744 0.649
0.6799 55.0 880 0.5996 0.5228 0.8536 0.4618 -1.0 0.5269 0.4525 0.5633 0.6531 0.6612 -1.0 0.6702 0.45 0.5228 0.6612
0.6799 56.0 896 0.6108 0.5096 0.8592 0.5195 -1.0 0.5159 0.4515 0.5612 0.6551 0.6633 -1.0 0.6723 0.45 0.5096 0.6633
0.6799 57.0 912 0.6771 0.4616 0.8561 0.4693 -1.0 0.4637 0.4515 0.5041 0.5959 0.6 -1.0 0.6064 0.45 0.4616 0.6
0.6799 58.0 928 0.6319 0.5014 0.8506 0.4776 -1.0 0.4973 0.601 0.5327 0.6388 0.651 -1.0 0.6532 0.6 0.5014 0.651
0.6799 59.0 944 0.6160 0.5157 0.8813 0.6142 -1.0 0.5155 0.605 0.5469 0.6714 0.6878 -1.0 0.6894 0.65 0.5157 0.6878
0.6799 60.0 960 0.5897 0.5435 0.9053 0.652 -1.0 0.544 0.6307 0.5735 0.6612 0.6673 -1.0 0.666 0.7 0.5435 0.6673
0.6799 61.0 976 0.6246 0.5216 0.8854 0.5715 -1.0 0.5225 0.5515 0.5347 0.6449 0.6531 -1.0 0.6574 0.55 0.5216 0.6531
0.6799 62.0 992 0.6032 0.5388 0.8834 0.6326 -1.0 0.548 0.4545 0.5612 0.6551 0.6612 -1.0 0.6681 0.5 0.5388 0.6612
0.3511 63.0 1008 0.5637 0.5601 0.883 0.6626 -1.0 0.5629 0.6307 0.5857 0.6755 0.6857 -1.0 0.6851 0.7 0.5601 0.6857
0.3511 64.0 1024 0.6113 0.5268 0.8727 0.6524 -1.0 0.5227 0.7 0.5592 0.6694 0.6837 -1.0 0.683 0.7 0.5268 0.6837
0.3511 65.0 1040 0.5917 0.5353 0.8891 0.5631 -1.0 0.5377 0.6 0.5673 0.6469 0.651 -1.0 0.6532 0.6 0.5353 0.651
0.3511 66.0 1056 0.6044 0.5139 0.8863 0.4967 -1.0 0.5181 0.5036 0.551 0.6735 0.6878 -1.0 0.6936 0.55 0.5139 0.6878
0.3511 67.0 1072 0.6213 0.4959 0.8897 0.437 -1.0 0.4974 0.6039 0.5224 0.6898 0.7041 -1.0 0.7064 0.65 0.4959 0.7041
0.3511 68.0 1088 0.6460 0.4848 0.8328 0.4619 -1.0 0.4845 0.6023 0.5224 0.6265 0.6306 -1.0 0.6298 0.65 0.4848 0.6306
0.3511 69.0 1104 0.5885 0.5244 0.8832 0.5448 -1.0 0.5279 0.5505 0.5531 0.6286 0.6347 -1.0 0.6383 0.55 0.5244 0.6347
0.3511 70.0 1120 0.6137 0.5355 0.8611 0.5569 -1.0 0.5358 0.601 0.5694 0.6429 0.6571 -1.0 0.6596 0.6 0.5355 0.6571
0.3511 71.0 1136 0.5859 0.5336 0.8925 0.5818 -1.0 0.5344 0.6252 0.5694 0.6408 0.649 -1.0 0.6489 0.65 0.5336 0.649
0.3511 72.0 1152 0.5771 0.5272 0.8664 0.583 -1.0 0.5289 0.6061 0.5551 0.6735 0.6878 -1.0 0.6872 0.7 0.5272 0.6878
0.3511 73.0 1168 0.6236 0.5035 0.885 0.5673 -1.0 0.506 0.504 0.5408 0.6408 0.649 -1.0 0.6532 0.55 0.5035 0.649
0.3511 74.0 1184 0.5987 0.5369 0.881 0.5568 -1.0 0.5369 0.6 0.5633 0.6408 0.6469 -1.0 0.6489 0.6 0.5369 0.6469
0.3511 75.0 1200 0.5919 0.5255 0.8927 0.5877 -1.0 0.5279 0.6 0.5633 0.6429 0.651 -1.0 0.6532 0.6 0.5255 0.651
0.3511 76.0 1216 0.6425 0.4919 0.8657 0.5759 -1.0 0.4884 0.6 0.498 0.6449 0.6714 -1.0 0.6745 0.6 0.4919 0.6714
0.3511 77.0 1232 0.6408 0.4998 0.8231 0.5352 -1.0 0.5053 0.468 0.5286 0.6327 0.6388 -1.0 0.6447 0.5 0.4998 0.6388
0.3511 78.0 1248 0.6273 0.5095 0.8546 0.5576 -1.0 0.5054 0.6692 0.5306 0.6571 0.6816 -1.0 0.6787 0.75 0.5095 0.6816
0.3511 79.0 1264 0.6202 0.5084 0.8796 0.5182 -1.0 0.5131 0.5524 0.5408 0.6388 0.649 -1.0 0.6511 0.6 0.5084 0.649
0.3511 80.0 1280 0.6160 0.5287 0.8642 0.5625 -1.0 0.5264 0.6505 0.5469 0.6735 0.6837 -1.0 0.6851 0.65 0.5287 0.6837
0.3511 81.0 1296 0.6104 0.4823 0.9057 0.4666 -1.0 0.493 0.4813 0.5163 0.6673 0.6857 -1.0 0.6894 0.6 0.4823 0.6857
0.3511 82.0 1312 0.6439 0.4926 0.8673 0.5554 -1.0 0.5002 0.5236 0.5347 0.649 0.651 -1.0 0.6532 0.6 0.4926 0.651
0.3511 83.0 1328 0.6153 0.5282 0.8787 0.5643 -1.0 0.5346 0.565 0.5347 0.6735 0.6939 -1.0 0.6936 0.7 0.5282 0.6939
0.3511 84.0 1344 0.5801 0.5364 0.8754 0.5112 -1.0 0.5383 0.6095 0.5633 0.6612 0.6714 -1.0 0.6702 0.7 0.5364 0.6714
0.3511 85.0 1360 0.5515 0.5736 0.9225 0.6315 -1.0 0.5774 0.6155 0.5837 0.6918 0.698 -1.0 0.6979 0.7 0.5736 0.698
0.3511 86.0 1376 0.5716 0.5533 0.9283 0.6293 -1.0 0.5607 0.5724 0.5653 0.6694 0.6755 -1.0 0.6745 0.7 0.5533 0.6755
0.3511 87.0 1392 0.5755 0.5518 0.8801 0.6059 -1.0 0.5516 0.6505 0.5551 0.6694 0.6735 -1.0 0.6745 0.65 0.5518 0.6735
0.3511 88.0 1408 0.5773 0.5592 0.909 0.5886 -1.0 0.5622 0.6175 0.5796 0.6878 0.6918 -1.0 0.6936 0.65 0.5592 0.6918
0.3511 89.0 1424 0.5885 0.5512 0.9047 0.6146 -1.0 0.5514 0.6615 0.5673 0.6551 0.6612 -1.0 0.6596 0.7 0.5512 0.6612
0.3511 90.0 1440 0.6344 0.5045 0.9065 0.5453 -1.0 0.4984 0.6836 0.5122 0.6612 0.6714 -1.0 0.666 0.8 0.5045 0.6714
0.3511 91.0 1456 0.5975 0.5389 0.8864 0.5947 -1.0 0.5423 0.6208 0.5388 0.6776 0.6857 -1.0 0.6872 0.65 0.5389 0.6857
0.3511 92.0 1472 0.6015 0.5212 0.8567 0.5014 -1.0 0.5221 0.6152 0.5531 0.6571 0.6653 -1.0 0.6617 0.75 0.5212 0.6653
0.3511 93.0 1488 0.6130 0.525 0.8885 0.6142 -1.0 0.5271 0.6154 0.551 0.6796 0.6918 -1.0 0.6915 0.7 0.525 0.6918
0.2568 94.0 1504 0.5796 0.5386 0.8917 0.5258 -1.0 0.5418 0.6197 0.5571 0.6694 0.6796 -1.0 0.6787 0.7 0.5386 0.6796
0.2568 95.0 1520 0.5950 0.5556 0.8887 0.6413 -1.0 0.5651 0.5779 0.5755 0.6653 0.6776 -1.0 0.6787 0.65 0.5556 0.6776
0.2568 96.0 1536 0.5935 0.5384 0.888 0.5717 -1.0 0.5411 0.6279 0.5776 0.6755 0.6837 -1.0 0.6809 0.75 0.5384 0.6837
0.2568 97.0 1552 0.6134 0.5331 0.8682 0.6411 -1.0 0.5349 0.6181 0.5551 0.6673 0.6714 -1.0 0.6702 0.7 0.5331 0.6714
0.2568 98.0 1568 0.5965 0.549 0.8901 0.6456 -1.0 0.5531 0.615 0.5735 0.6612 0.6673 -1.0 0.666 0.7 0.549 0.6673
0.2568 99.0 1584 0.5537 0.5678 0.8895 0.6812 -1.0 0.5729 0.6153 0.5918 0.6816 0.7 -1.0 0.7 0.7 0.5678 0.7
0.2568 100.0 1600 0.5526 0.5808 0.8989 0.6999 -1.0 0.5826 0.6252 0.5878 0.6959 0.7061 -1.0 0.7085 0.65 0.5808 0.7061
0.2568 101.0 1616 0.5909 0.5341 0.9003 0.5713 -1.0 0.5403 0.5669 0.5531 0.6918 0.702 -1.0 0.7 0.75 0.5341 0.702
0.2568 102.0 1632 0.5938 0.5453 0.8969 0.5621 -1.0 0.5524 0.5858 0.5776 0.6939 0.7 -1.0 0.7 0.7 0.5453 0.7
0.2568 103.0 1648 0.5580 0.5832 0.9002 0.6741 -1.0 0.5925 0.6257 0.602 0.6898 0.698 -1.0 0.7 0.65 0.5832 0.698
0.2568 104.0 1664 0.5525 0.5697 0.9022 0.617 -1.0 0.5757 0.6053 0.6 0.7061 0.7163 -1.0 0.717 0.7 0.5697 0.7163
0.2568 105.0 1680 0.5932 0.5448 0.8957 0.6301 -1.0 0.5424 0.667 0.5571 0.651 0.6653 -1.0 0.6638 0.7 0.5448 0.6653
0.2568 106.0 1696 0.5683 0.569 0.8945 0.6047 -1.0 0.58 0.5846 0.5918 0.6939 0.702 -1.0 0.7021 0.7 0.569 0.702
0.2568 107.0 1712 0.5586 0.5787 0.8984 0.7182 -1.0 0.5859 0.6179 0.5898 0.698 0.7143 -1.0 0.7128 0.75 0.5787 0.7143
0.2568 108.0 1728 0.5691 0.5686 0.8999 0.6004 -1.0 0.5697 0.6654 0.5898 0.7 0.7122 -1.0 0.7106 0.75 0.5686 0.7122
0.2568 109.0 1744 0.5906 0.5323 0.897 0.5502 -1.0 0.5379 0.5828 0.5551 0.6571 0.6612 -1.0 0.6596 0.7 0.5323 0.6612
0.2568 110.0 1760 0.5844 0.5495 0.8792 0.6197 -1.0 0.5573 0.5702 0.5796 0.6653 0.6755 -1.0 0.6766 0.65 0.5495 0.6755
0.2568 111.0 1776 0.5794 0.562 0.8869 0.7004 -1.0 0.5669 0.6196 0.5918 0.6878 0.7 -1.0 0.6979 0.75 0.562 0.7
0.2568 112.0 1792 0.5813 0.5511 0.8906 0.6147 -1.0 0.559 0.5688 0.5857 0.6694 0.6735 -1.0 0.6745 0.65 0.5511 0.6735
0.2568 113.0 1808 0.5894 0.5586 0.8849 0.6145 -1.0 0.565 0.6261 0.5878 0.6735 0.6816 -1.0 0.6809 0.7 0.5586 0.6816
0.2568 114.0 1824 0.5810 0.5615 0.8868 0.656 -1.0 0.5671 0.6174 0.5898 0.6816 0.6939 -1.0 0.6915 0.75 0.5615 0.6939
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0.0121 283.0 4528 0.5541 0.5838 0.8972 0.6373 -1.0 0.5939 0.6248 0.6 0.702 0.7102 -1.0 0.7085 0.75 0.5838 0.7102
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0.0121 287.0 4592 0.5547 0.5838 0.8972 0.6373 -1.0 0.5939 0.6248 0.6 0.702 0.7102 -1.0 0.7085 0.75 0.5838 0.7102
0.0121 288.0 4608 0.5544 0.584 0.8972 0.6382 -1.0 0.5941 0.6248 0.6 0.702 0.7102 -1.0 0.7085 0.75 0.584 0.7102
0.0121 289.0 4624 0.5546 0.584 0.8972 0.6382 -1.0 0.5941 0.6248 0.6 0.702 0.7102 -1.0 0.7085 0.75 0.584 0.7102
0.0121 290.0 4640 0.5547 0.5846 0.8972 0.6382 -1.0 0.5947 0.6248 0.6 0.702 0.7102 -1.0 0.7085 0.75 0.5846 0.7102
0.0121 291.0 4656 0.5547 0.584 0.8972 0.6382 -1.0 0.5941 0.6248 0.6 0.702 0.7102 -1.0 0.7085 0.75 0.584 0.7102
0.0121 292.0 4672 0.5546 0.584 0.8972 0.6382 -1.0 0.5941 0.6248 0.6 0.702 0.7102 -1.0 0.7085 0.75 0.584 0.7102
0.0121 293.0 4688 0.5546 0.584 0.8972 0.6382 -1.0 0.5941 0.6248 0.6 0.702 0.7102 -1.0 0.7085 0.75 0.584 0.7102
0.0121 294.0 4704 0.5547 0.5846 0.8972 0.6382 -1.0 0.5947 0.6248 0.6 0.702 0.7102 -1.0 0.7085 0.75 0.5846 0.7102
0.0121 295.0 4720 0.5547 0.5846 0.8972 0.6382 -1.0 0.5947 0.6248 0.6 0.702 0.7102 -1.0 0.7085 0.75 0.5846 0.7102
0.0121 296.0 4736 0.5546 0.5846 0.8972 0.6382 -1.0 0.5947 0.6248 0.6 0.702 0.7102 -1.0 0.7085 0.75 0.5846 0.7102
0.0121 297.0 4752 0.5546 0.584 0.8972 0.6382 -1.0 0.5941 0.6248 0.6 0.702 0.7102 -1.0 0.7085 0.75 0.584 0.7102
0.0121 298.0 4768 0.5546 0.5846 0.8972 0.6382 -1.0 0.5947 0.6248 0.6 0.702 0.7102 -1.0 0.7085 0.75 0.5846 0.7102
0.0121 299.0 4784 0.5546 0.5846 0.8972 0.6382 -1.0 0.5947 0.6248 0.6 0.702 0.7102 -1.0 0.7085 0.75 0.5846 0.7102
0.0121 300.0 4800 0.5546 0.5846 0.8972 0.6382 -1.0 0.5947 0.6248 0.6 0.702 0.7102 -1.0 0.7085 0.75 0.5846 0.7102

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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