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kvasir_seg_rtdetr_r18

Object Detection
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rt_detr_v2
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kvasir_seg_rtdetr_r18

This model is a fine-tuned version of PekingU/rtdetr_r18vd_coco_o365 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 4.8559
  • Map: 0.6996
  • Map 50: 0.9114
  • Map 75: 0.768
  • Map Small: 0.0
  • Map Medium: 0.4886
  • Map Large: 0.7135
  • Mar 1: 0.7199
  • Mar 10: 0.8393
  • Mar 100: 0.8915
  • Mar Small: 0.0
  • Mar Medium: 0.84
  • Mar Large: 0.8985
  • Map Polyp: 0.6996
  • Mar 100 Polyp: 0.8915

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: 0.0001
  • train_batch_size: 8
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 300
  • num_epochs: 150

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 Polyp Mar 100 Polyp
328.7584 1.0 100 105.4353 0.0217 0.0467 0.0164 0.0 0.0 0.0235 0.0844 0.2213 0.2839 0.0 0.0 0.2995 0.0217 0.2839
54.5087 2.0 200 29.3093 0.0641 0.1127 0.0625 0.0 0.1482 0.0671 0.2147 0.5171 0.6886 0.0 0.24 0.7145 0.0641 0.6886
18.273 3.0 300 13.9644 0.195 0.2841 0.2099 0.0 0.0152 0.2089 0.3654 0.6815 0.7872 0.0 0.59 0.801 0.195 0.7872
12.3686 4.0 400 9.2201 0.2061 0.2977 0.2192 0.0 0.0328 0.2194 0.3621 0.7118 0.8924 0.0 0.7 0.9065 0.2061 0.8924
10.3152 5.0 500 7.9569 0.4353 0.561 0.4655 0.0 0.1308 0.4571 0.5218 0.7815 0.8905 0.0 0.65 0.907 0.4353 0.8905
9.877 6.0 600 8.6031 0.3128 0.399 0.3417 0.0 0.1584 0.3279 0.4848 0.7682 0.91 0.0 0.76 0.922 0.3128 0.91
9.3949 7.0 700 7.6619 0.5258 0.7045 0.5629 0.0 0.1969 0.5489 0.5844 0.7763 0.9185 0.0 0.67 0.9355 0.5258 0.9185
8.9883 8.0 800 7.7975 0.4233 0.57 0.4376 0.0 0.1904 0.4408 0.5422 0.791 0.9128 0.0 0.82 0.922 0.4233 0.9128
8.5345 9.0 900 7.6628 0.2454 0.3437 0.2641 0.0 0.2014 0.2574 0.391 0.7118 0.9028 0.0 0.75 0.915 0.2454 0.9028
8.3354 10.0 1000 8.2167 0.2949 0.4087 0.3156 0.0 0.1208 0.3114 0.4507 0.7199 0.8872 0.0 0.6 0.906 0.2949 0.8872
8.044 11.0 1100 7.1574 0.4414 0.5745 0.4718 0.0 0.2895 0.461 0.5569 0.7905 0.9076 0.0 0.78 0.9185 0.4414 0.9076
8.0058 12.0 1200 7.0897 0.344 0.4723 0.3711 0.0 0.2359 0.3603 0.5246 0.8232 0.9137 0.0 0.78 0.925 0.344 0.9137
7.8317 13.0 1300 7.3114 0.3671 0.5186 0.3898 0.0 0.1734 0.3846 0.5351 0.7711 0.9081 0.0 0.8 0.918 0.3671 0.9081
7.5776 14.0 1400 7.5346 0.3043 0.4337 0.3217 0.0 0.1102 0.3199 0.473 0.7773 0.9109 0.0 0.79 0.9215 0.3043 0.9109
7.367 15.0 1500 6.6930 0.4188 0.5544 0.4475 0.0 0.2315 0.4357 0.546 0.8142 0.9218 0.0 0.84 0.9305 0.4188 0.9218
7.249 16.0 1600 6.7257 0.4509 0.6084 0.4975 0.0 0.2494 0.4683 0.5981 0.8469 0.909 0.0 0.8 0.919 0.4509 0.909
7.1063 17.0 1700 7.8123 0.3076 0.4209 0.3293 0.0 0.1455 0.3224 0.4943 0.7412 0.9043 0.0 0.77 0.9155 0.3076 0.9043
7.1784 18.0 1800 7.4297 0.3582 0.4877 0.3739 0.0 0.1887 0.3749 0.5071 0.7962 0.9166 0.0 0.74 0.93 0.3582 0.9166
7.0446 19.0 1900 7.1160 0.3486 0.4704 0.3853 0.0 0.203 0.3635 0.5555 0.7957 0.909 0.0 0.78 0.92 0.3486 0.909
7.0708 20.0 2000 6.9090 0.4352 0.6138 0.4673 0.0 0.1152 0.455 0.5341 0.7995 0.9185 0.0 0.87 0.9255 0.4352 0.9185
7.0069 21.0 2100 6.4302 0.4221 0.5845 0.439 0.0 0.1887 0.44 0.5038 0.828 0.9194 0.0 0.8 0.93 0.4221 0.9194
6.9179 22.0 2200 6.8735 0.2883 0.4071 0.3019 0.0 0.1738 0.301 0.4047 0.7839 0.9009 0.0 0.77 0.912 0.2883 0.9009
6.7794 23.0 2300 6.9011 0.4379 0.6018 0.481 0.0 0.1178 0.4587 0.5265 0.7915 0.9052 0.0 0.8 0.915 0.4379 0.9052
6.9367 24.0 2400 5.8450 0.5848 0.7835 0.6384 0.0 0.1811 0.61 0.6313 0.8398 0.9171 0.0 0.77 0.929 0.5848 0.9171
6.8596 25.0 2500 6.6438 0.3867 0.5434 0.4014 0.0 0.173 0.4041 0.5246 0.7773 0.8995 0.0 0.77 0.9105 0.3867 0.8995
6.7357 26.0 2600 7.0414 0.4158 0.5564 0.4631 0.0 0.2366 0.4349 0.5796 0.7967 0.8948 0.0 0.72 0.908 0.4158 0.8948
6.7968 27.0 2700 6.7433 0.528 0.7024 0.5641 0.0 0.1794 0.5525 0.6123 0.8573 0.9209 0.0 0.79 0.932 0.528 0.9209
6.5425 28.0 2800 6.8662 0.4346 0.587 0.4484 0.0 0.1637 0.4535 0.6251 0.828 0.9109 0.0 0.82 0.92 0.4346 0.9109
6.6149 29.0 2900 7.1492 0.4277 0.5659 0.4601 0.0 0.357 0.4467 0.5716 0.8237 0.9114 0.0 0.77 0.923 0.4277 0.9114
6.4956 30.0 3000 6.4835 0.4805 0.6497 0.5108 0.0 0.2116 0.5006 0.6493 0.8431 0.9081 0.0 0.78 0.919 0.4805 0.9081
6.325 31.0 3100 6.4725 0.4354 0.5666 0.4718 0.0 0.3062 0.4543 0.6327 0.8403 0.9114 0.0 0.77 0.923 0.4354 0.9114
6.4792 32.0 3200 6.5891 0.4733 0.6166 0.4951 0.0 0.1749 0.4961 0.646 0.8355 0.9118 0.0 0.77 0.9235 0.4733 0.9118
6.4267 33.0 3300 6.2471 0.5297 0.6574 0.584 0.0 0.417 0.5506 0.6559 0.8649 0.91 0.0 0.72 0.924 0.5297 0.91
6.4015 34.0 3400 6.2159 0.5927 0.7575 0.6442 0.0 0.3905 0.614 0.6559 0.8393 0.9071 0.0 0.85 0.9145 0.5927 0.9071
6.2961 35.0 3500 6.9543 0.4289 0.6037 0.45 0.0 0.3703 0.442 0.4882 0.7972 0.8815 0.0 0.81 0.8895 0.4289 0.8815
6.1437 36.0 3600 6.2903 0.5107 0.6672 0.5503 0.0 0.1753 0.5298 0.6137 0.8436 0.9095 0.0 0.8 0.9195 0.5107 0.9095
6.1999 37.0 3700 6.4701 0.465 0.6323 0.4888 0.0 0.2612 0.4825 0.5555 0.7877 0.8905 0.0 0.81 0.899 0.465 0.8905
6.1331 38.0 3800 6.0898 0.461 0.6161 0.4959 0.0 0.1816 0.4799 0.6327 0.8218 0.9 0.0 0.79 0.91 0.461 0.9
6.1776 39.0 3900 6.2661 0.468 0.6355 0.502 0.0 0.3374 0.486 0.546 0.8232 0.9062 0.0 0.8 0.916 0.468 0.9062
6.018 40.0 4000 5.8017 0.5797 0.7618 0.6432 0.0 0.2132 0.6023 0.6038 0.8445 0.9043 0.0 0.85 0.9115 0.5797 0.9043
6.1899 41.0 4100 5.7870 0.5732 0.7472 0.6297 0.0 0.1139 0.5978 0.6517 0.836 0.9047 0.0 0.85 0.912 0.5732 0.9047
5.9885 42.0 4200 5.8262 0.6162 0.793 0.6722 0.0 0.36 0.6394 0.637 0.8573 0.9076 0.0 0.83 0.916 0.6162 0.9076
5.9469 43.0 4300 5.9656 0.5803 0.7559 0.622 0.0 0.4129 0.603 0.6483 0.8384 0.9047 0.0 0.85 0.912 0.5803 0.9047
5.9479 44.0 4400 6.0606 0.5878 0.7564 0.6396 0.0 0.3012 0.6089 0.6066 0.8479 0.9043 0.0 0.84 0.912 0.5878 0.9043
5.8736 45.0 4500 6.1277 0.5992 0.7708 0.6414 0.0 0.25 0.6238 0.6588 0.8474 0.9071 0.0 0.83 0.9155 0.5992 0.9071
6.0308 46.0 4600 6.0510 0.5644 0.7258 0.6109 0.0 0.3322 0.5876 0.6626 0.8474 0.9014 0.0 0.85 0.9085 0.5644 0.9014
5.8821 47.0 4700 6.1862 0.5191 0.651 0.5563 0.0 0.1103 0.5429 0.6441 0.8384 0.9114 0.0 0.82 0.9205 0.5191 0.9114
5.8174 48.0 4800 6.2716 0.5513 0.7038 0.5877 0.0 0.1605 0.5752 0.6398 0.8526 0.9142 0.0 0.84 0.9225 0.5513 0.9142
5.8138 49.0 4900 6.0443 0.5792 0.7603 0.6092 0.0 0.3321 0.5998 0.6393 0.8346 0.8981 0.0 0.79 0.908 0.5792 0.8981
5.8482 50.0 5000 6.5761 0.4936 0.6482 0.5428 0.0 0.289 0.5163 0.5758 0.7943 0.8896 0.0 0.75 0.901 0.4936 0.8896
5.7062 51.0 5100 6.1185 0.5283 0.6686 0.5753 0.0 0.3035 0.5505 0.6232 0.8341 0.9118 0.0 0.87 0.9185 0.5283 0.9118
5.6989 52.0 5200 6.0044 0.5856 0.7479 0.6369 0.0 0.2705 0.6085 0.6844 0.8308 0.8962 0.0 0.82 0.9045 0.5856 0.8962
5.5779 53.0 5300 5.9162 0.6011 0.77 0.6466 0.0 0.3969 0.6239 0.7028 0.8536 0.9 0.0 0.84 0.9075 0.6011 0.9
5.5422 54.0 5400 6.1687 0.5609 0.7387 0.6005 0.0 0.2592 0.5814 0.6218 0.8336 0.8995 0.0 0.84 0.907 0.5609 0.8995
5.5615 55.0 5500 7.0190 0.456 0.631 0.4893 0.0 0.3124 0.4725 0.5336 0.8024 0.8886 0.0 0.83 0.896 0.456 0.8886
5.5674 56.0 5600 6.3056 0.5218 0.7175 0.5431 0.0 0.4512 0.5397 0.6318 0.837 0.8967 0.0 0.86 0.903 0.5218 0.8967
5.4516 57.0 5700 5.6783 0.6161 0.8042 0.6533 0.0 0.4324 0.6357 0.6716 0.8469 0.9 0.0 0.87 0.906 0.6161 0.9
5.415 58.0 5800 5.9260 0.6019 0.7819 0.6293 0.0 0.4337 0.6246 0.6725 0.8408 0.9009 0.0 0.83 0.909 0.6019 0.9009
5.5503 59.0 5900 6.1504 0.5291 0.7104 0.5634 0.0 0.4015 0.5479 0.591 0.8502 0.9014 0.0 0.82 0.91 0.5291 0.9014
5.4917 60.0 6000 5.8398 0.5809 0.7735 0.6137 0.0 0.3969 0.6001 0.6474 0.8573 0.8934 0.0 0.79 0.903 0.5809 0.8934
5.5592 61.0 6100 5.7688 0.611 0.7941 0.6522 0.0 0.3962 0.6297 0.6408 0.8403 0.8995 0.0 0.84 0.907 0.611 0.8995
5.3401 62.0 6200 5.7462 0.5848 0.775 0.5963 0.0 0.4851 0.6033 0.6536 0.8474 0.9047 0.0 0.88 0.9105 0.5848 0.9047
5.3558 63.0 6300 5.8356 0.5816 0.7882 0.619 0.0 0.4334 0.5982 0.6332 0.8223 0.8791 0.0 0.9 0.8825 0.5816 0.8791
5.326 64.0 6400 6.2211 0.5195 0.707 0.5443 0.0 0.3136 0.5373 0.5886 0.8256 0.8877 0.0 0.83 0.895 0.5195 0.8877
5.278 65.0 6500 5.3357 0.6396 0.8254 0.6918 0.0 0.473 0.6568 0.6773 0.8545 0.8986 0.0 0.87 0.9045 0.6396 0.8986
5.315 66.0 6600 5.8402 0.6183 0.8016 0.6708 0.0 0.4752 0.6386 0.6616 0.8602 0.9005 0.0 0.87 0.9065 0.6183 0.9005
5.3418 67.0 6700 5.4617 0.6167 0.8373 0.6565 0.0 0.4112 0.6353 0.6588 0.8474 0.8981 0.0 0.85 0.905 0.6167 0.8981
5.2841 68.0 6800 5.4826 0.6696 0.8578 0.7252 0.0 0.3299 0.6891 0.6882 0.8526 0.8981 0.0 0.87 0.904 0.6696 0.8981
5.2984 69.0 6900 5.4558 0.6553 0.866 0.6974 0.0 0.4049 0.671 0.6863 0.8355 0.9 0.0 0.88 0.9055 0.6553 0.9
5.1851 70.0 7000 5.9259 0.5741 0.7469 0.6277 0.0 0.2257 0.5971 0.6161 0.8303 0.8934 0.0 0.86 0.8995 0.5741 0.8934
5.181 71.0 7100 5.4635 0.6607 0.8592 0.7119 0.0 0.4913 0.6761 0.6806 0.8412 0.9024 0.0 0.84 0.91 0.6607 0.9024
5.1508 72.0 7200 5.6232 0.611 0.8037 0.6533 0.0 0.4713 0.6282 0.654 0.8422 0.9052 0.0 0.89 0.9105 0.611 0.9052
5.1352 73.0 7300 5.6329 0.6132 0.818 0.6484 0.0 0.5055 0.6291 0.6659 0.8408 0.8948 0.0 0.84 0.902 0.6132 0.8948
5.0835 74.0 7400 5.2254 0.6655 0.862 0.7302 0.0 0.4657 0.6816 0.6948 0.8545 0.8991 0.0 0.88 0.9045 0.6655 0.8991
5.0506 75.0 7500 5.5285 0.6407 0.8335 0.6843 0.0 0.3756 0.6603 0.6673 0.8559 0.9052 0.0 0.87 0.9115 0.6407 0.9052
5.0889 76.0 7600 5.6099 0.604 0.8039 0.6636 0.0 0.4564 0.6204 0.6583 0.8308 0.8924 0.0 0.86 0.8985 0.604 0.8924
5.0013 77.0 7700 5.2094 0.6616 0.863 0.7203 0.0 0.3771 0.6808 0.6962 0.8479 0.8896 0.0 0.85 0.896 0.6616 0.8896
5.1114 78.0 7800 5.1092 0.6651 0.8656 0.7255 0.0 0.4837 0.6786 0.6882 0.8488 0.8891 0.0 0.85 0.8955 0.6651 0.8891
5.0461 79.0 7900 5.1339 0.6623 0.8689 0.718 0.0 0.4655 0.6796 0.6962 0.8455 0.9033 0.0 0.86 0.91 0.6623 0.9033
5.0452 80.0 8000 5.3328 0.6569 0.8528 0.7302 0.0 0.4636 0.6762 0.6948 0.8469 0.8972 0.0 0.88 0.9025 0.6569 0.8972
5.0501 81.0 8100 5.5217 0.6503 0.8424 0.6965 0.0 0.408 0.6679 0.673 0.8431 0.8957 0.0 0.86 0.902 0.6503 0.8957
4.9118 82.0 8200 5.6498 0.6337 0.8333 0.6797 0.0 0.3812 0.6538 0.6597 0.8289 0.8938 0.0 0.84 0.901 0.6337 0.8938
4.971 83.0 8300 5.7732 0.6249 0.823 0.6661 0.0 0.467 0.6435 0.6559 0.8389 0.891 0.0 0.78 0.901 0.6249 0.891
4.8744 84.0 8400 5.3769 0.678 0.8753 0.738 0.0 0.4127 0.6943 0.6981 0.8517 0.9005 0.0 0.9 0.905 0.678 0.9005
4.9024 85.0 8500 5.2106 0.6799 0.8813 0.7143 0.0 0.392 0.6986 0.7033 0.8427 0.8943 0.0 0.84 0.9015 0.6799 0.8943
4.8361 86.0 8600 5.1924 0.6726 0.8596 0.7193 0.0 0.3602 0.6921 0.6981 0.8521 0.9005 0.0 0.86 0.907 0.6726 0.9005
4.7713 87.0 8700 5.2097 0.6786 0.8854 0.7263 0.0 0.389 0.6958 0.6853 0.8488 0.8991 0.0 0.87 0.905 0.6786 0.8991
4.8765 88.0 8800 5.4051 0.6566 0.8497 0.7137 0.0 0.4111 0.6757 0.6773 0.8398 0.8825 0.0 0.82 0.89 0.6566 0.8825
4.7893 89.0 8900 5.3679 0.6497 0.8468 0.7021 0.0 0.4852 0.6671 0.6886 0.8393 0.8967 0.0 0.86 0.903 0.6497 0.8967
4.7177 90.0 9000 5.3805 0.6533 0.8489 0.7066 0.0 0.4542 0.6711 0.6919 0.8313 0.8915 0.0 0.82 0.8995 0.6533 0.8915
4.7715 91.0 9100 5.6189 0.6267 0.8128 0.6736 0.0 0.4737 0.6424 0.6564 0.8427 0.8967 0.0 0.86 0.903 0.6267 0.8967
4.7119 92.0 9200 5.5511 0.6398 0.8312 0.6803 0.0 0.5786 0.6559 0.6526 0.8318 0.8929 0.0 0.83 0.9005 0.6398 0.8929
4.695 93.0 9300 5.5682 0.6327 0.8241 0.667 0.0 0.4086 0.6499 0.6716 0.8327 0.8924 0.0 0.85 0.899 0.6327 0.8924
4.6644 94.0 9400 5.3228 0.662 0.855 0.6994 0.0 0.3843 0.68 0.6858 0.8464 0.8962 0.0 0.87 0.902 0.662 0.8962
4.6613 95.0 9500 5.2617 0.6644 0.8642 0.7088 0.0 0.5257 0.6779 0.6929 0.8488 0.8981 0.0 0.83 0.906 0.6644 0.8981
4.6428 96.0 9600 5.0369 0.6893 0.8848 0.7569 0.0 0.4619 0.7064 0.709 0.8583 0.8934 0.0 0.82 0.9015 0.6893 0.8934
4.6383 97.0 9700 5.3712 0.6373 0.8179 0.6922 0.0 0.4024 0.6536 0.6664 0.8488 0.8991 0.0 0.89 0.904 0.6373 0.8991
4.6614 98.0 9800 5.2165 0.6599 0.857 0.7168 0.0 0.3705 0.6784 0.6891 0.8403 0.8882 0.0 0.86 0.894 0.6599 0.8882
4.6073 99.0 9900 5.2039 0.6479 0.8478 0.6905 0.0 0.4192 0.666 0.6825 0.8445 0.8877 0.0 0.83 0.895 0.6479 0.8877
4.5726 100.0 10000 5.2745 0.663 0.8686 0.7038 0.0 0.4939 0.6774 0.6886 0.8431 0.8848 0.0 0.85 0.891 0.663 0.8848
4.5516 101.0 10100 5.1948 0.6682 0.8786 0.7233 0.0 0.5113 0.6813 0.7066 0.8389 0.8863 0.0 0.87 0.8915 0.6682 0.8863
4.5178 102.0 10200 5.0016 0.6808 0.8885 0.7253 0.0 0.4145 0.6975 0.6991 0.8398 0.8882 0.0 0.88 0.893 0.6808 0.8882
4.554 103.0 10300 5.1041 0.6713 0.8764 0.7146 0.0 0.484 0.6839 0.7028 0.8365 0.8896 0.0 0.87 0.895 0.6713 0.8896
4.5047 104.0 10400 5.0536 0.6733 0.8881 0.7346 0.0 0.5161 0.6861 0.69 0.8313 0.8801 0.0 0.84 0.8865 0.6733 0.8801
4.4769 105.0 10500 5.0607 0.6881 0.9005 0.7435 0.0 0.5438 0.6998 0.7137 0.8389 0.882 0.0 0.82 0.8895 0.6881 0.882
4.4684 106.0 10600 5.0023 0.6854 0.8926 0.7468 0.0 0.5582 0.6987 0.718 0.8408 0.8953 0.0 0.82 0.9035 0.6854 0.8953
4.5203 107.0 10700 5.0049 0.6807 0.8826 0.7457 0.0 0.554 0.6952 0.7171 0.8645 0.8943 0.0 0.83 0.902 0.6807 0.8943
4.413 108.0 10800 4.9532 0.6846 0.8939 0.7492 0.0 0.5038 0.6991 0.718 0.8403 0.8915 0.0 0.81 0.9 0.6846 0.8915
4.4614 109.0 10900 4.9174 0.6956 0.8992 0.7565 0.0 0.4832 0.7107 0.7218 0.8427 0.8953 0.0 0.84 0.9025 0.6956 0.8953
4.4055 110.0 11000 5.0199 0.6802 0.8868 0.7409 0.0 0.4514 0.6963 0.7076 0.8346 0.8991 0.0 0.82 0.9075 0.6802 0.8991
4.3637 111.0 11100 4.9812 0.6814 0.8892 0.7393 0.0 0.5097 0.696 0.7171 0.8469 0.8919 0.0 0.79 0.9015 0.6814 0.8919
4.4024 112.0 11200 4.9323 0.6884 0.9042 0.7445 0.0 0.5403 0.7008 0.7133 0.845 0.8915 0.0 0.82 0.8995 0.6884 0.8915
4.3255 113.0 11300 4.8589 0.6922 0.9051 0.7643 0.0 0.5214 0.7066 0.7114 0.8417 0.8905 0.0 0.82 0.8985 0.6922 0.8905
4.3582 114.0 11400 4.9238 0.6879 0.9075 0.749 0.0 0.4796 0.7023 0.7147 0.8374 0.8877 0.0 0.81 0.896 0.6879 0.8877
4.287 115.0 11500 4.9863 0.6886 0.9018 0.7404 0.0 0.4966 0.703 0.7166 0.8408 0.8867 0.0 0.83 0.894 0.6886 0.8867
4.3159 116.0 11600 5.0250 0.6752 0.8889 0.7215 0.0 0.5872 0.6885 0.6948 0.8455 0.8948 0.0 0.82 0.903 0.6752 0.8948
4.3536 117.0 11700 4.8935 0.6867 0.8959 0.7413 0.0 0.4453 0.7024 0.7142 0.8398 0.8872 0.0 0.82 0.895 0.6867 0.8872
4.2804 118.0 11800 4.9059 0.6874 0.9026 0.7391 0.0 0.4907 0.701 0.7137 0.8403 0.8919 0.0 0.84 0.899 0.6874 0.8919
4.2833 119.0 11900 4.9931 0.679 0.8909 0.7321 0.0 0.5342 0.6925 0.7085 0.846 0.8953 0.0 0.84 0.9025 0.679 0.8953
4.294 120.0 12000 4.9152 0.6839 0.8974 0.7506 0.0 0.5001 0.6977 0.728 0.8469 0.8877 0.0 0.83 0.895 0.6839 0.8877
4.2876 121.0 12100 4.8559 0.6996 0.9114 0.768 0.0 0.4886 0.7135 0.7199 0.8393 0.8915 0.0 0.84 0.8985 0.6996 0.8915
4.3188 122.0 12200 5.0836 0.6661 0.8779 0.7081 0.0 0.5014 0.6801 0.6981 0.8403 0.8919 0.0 0.83 0.8995 0.6661 0.8919
4.2945 123.0 12300 4.9716 0.6945 0.9015 0.7443 0.0 0.5274 0.7081 0.7185 0.8436 0.8929 0.0 0.83 0.9005 0.6945 0.8929
4.2278 124.0 12400 4.9418 0.686 0.8984 0.7362 0.0 0.4882 0.6988 0.7204 0.8469 0.8867 0.0 0.83 0.894 0.686 0.8867
4.2593 125.0 12500 5.0332 0.686 0.9005 0.7381 0.0 0.5344 0.6971 0.7209 0.8408 0.8858 0.0 0.85 0.892 0.686 0.8858
4.2182 126.0 12600 4.9317 0.6852 0.8955 0.7404 0.0 0.5508 0.6976 0.7223 0.8441 0.8886 0.0 0.84 0.8955 0.6852 0.8886
4.2638 127.0 12700 5.0511 0.6708 0.8849 0.7274 0.0 0.5834 0.683 0.7123 0.8393 0.8886 0.0 0.85 0.895 0.6708 0.8886
4.1952 128.0 12800 5.0145 0.6722 0.889 0.7223 0.0 0.5595 0.6845 0.7052 0.8346 0.8825 0.0 0.84 0.889 0.6722 0.8825
4.2047 129.0 12900 4.9855 0.6842 0.8966 0.732 0.0 0.5326 0.6973 0.7175 0.8398 0.8806 0.0 0.84 0.887 0.6842 0.8806
4.215 130.0 13000 4.9706 0.6808 0.8958 0.7319 0.0 0.5291 0.6942 0.7114 0.8332 0.8877 0.0 0.83 0.895 0.6808 0.8877
4.2377 131.0 13100 4.9718 0.6839 0.898 0.7366 0.0 0.5537 0.6973 0.7104 0.8351 0.881 0.0 0.82 0.8885 0.6839 0.881
4.1521 132.0 13200 4.9658 0.6859 0.8964 0.745 0.0 0.5394 0.6986 0.7152 0.8384 0.8801 0.0 0.85 0.886 0.6859 0.8801
4.205 133.0 13300 4.9849 0.6792 0.8912 0.7382 0.0 0.4949 0.693 0.7081 0.8322 0.8839 0.0 0.83 0.891 0.6792 0.8839
4.1716 134.0 13400 4.9999 0.6804 0.8935 0.7385 0.0 0.4934 0.6937 0.7038 0.8408 0.8834 0.0 0.82 0.891 0.6804 0.8834
4.1556 135.0 13500 5.0120 0.6811 0.8936 0.7433 0.0 0.5101 0.6943 0.7019 0.8417 0.8815 0.0 0.82 0.889 0.6811 0.8815
4.1656 136.0 13600 5.0309 0.674 0.8867 0.7315 0.0 0.5147 0.6871 0.7066 0.8365 0.882 0.0 0.84 0.8885 0.674 0.882
4.1715 137.0 13700 4.9570 0.6795 0.8966 0.7313 0.0 0.4992 0.6932 0.7109 0.8313 0.8834 0.0 0.83 0.8905 0.6795 0.8834
4.1291 138.0 13800 4.9760 0.6796 0.8925 0.7315 0.0 0.511 0.6934 0.7161 0.8336 0.8872 0.0 0.84 0.894 0.6796 0.8872
4.1406 139.0 13900 4.9690 0.6851 0.8992 0.7308 0.0 0.5089 0.6988 0.7114 0.8294 0.8815 0.0 0.84 0.888 0.6851 0.8815
4.1242 140.0 14000 4.9718 0.6788 0.8946 0.7239 0.0 0.4992 0.6924 0.7038 0.8322 0.8829 0.0 0.84 0.8895 0.6788 0.8829
4.1337 141.0 14100 4.9832 0.6771 0.8921 0.7255 0.0 0.4862 0.6907 0.7095 0.8355 0.882 0.0 0.82 0.8895 0.6771 0.882
4.1766 142.0 14200 4.9979 0.6767 0.8893 0.7238 0.0 0.5086 0.6902 0.7147 0.8403 0.8834 0.0 0.84 0.89 0.6767 0.8834
4.158 143.0 14300 4.9638 0.6823 0.8977 0.7327 0.0 0.5184 0.6953 0.7104 0.8351 0.8863 0.0 0.84 0.893 0.6823 0.8863
4.1759 144.0 14400 4.9966 0.6756 0.8865 0.7228 0.0 0.5223 0.6885 0.7071 0.8384 0.8825 0.0 0.84 0.889 0.6756 0.8825
4.122 145.0 14500 4.9467 0.6819 0.8952 0.7302 0.0 0.5193 0.695 0.7152 0.8379 0.8858 0.0 0.83 0.893 0.6819 0.8858
4.1834 146.0 14600 4.9808 0.6808 0.895 0.7261 0.0 0.5239 0.6937 0.7057 0.8322 0.8867 0.0 0.83 0.894 0.6808 0.8867
4.1443 147.0 14700 4.9647 0.6848 0.9002 0.7371 0.0 0.5254 0.6979 0.7076 0.837 0.8825 0.0 0.84 0.889 0.6848 0.8825
4.1243 148.0 14800 5.0032 0.6754 0.8847 0.7296 0.0 0.525 0.6883 0.7104 0.8389 0.8844 0.0 0.84 0.891 0.6754 0.8844
4.1306 149.0 14900 4.9693 0.6777 0.8919 0.7318 0.0 0.5181 0.6902 0.7118 0.8336 0.8848 0.0 0.84 0.8915 0.6777 0.8848
4.1316 150.0 15000 5.0121 0.6732 0.8882 0.7185 0.0 0.5121 0.6864 0.7137 0.8332 0.8834 0.0 0.84 0.89 0.6732 0.8834

Framework versions

  • Transformers 4.53.0.dev0
  • Pytorch 2.7.1+cu126
  • Datasets 3.6.0
  • Tokenizers 0.21.1
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