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RMBG-human_parsing-finetuned

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RMBG-human_parsing-finetuned

This model is a fine-tuned version of briaai/RMBG-1.4 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7383
  • Mean Iou: 0.0018
  • Mean Accuracy: 0.0020
  • Overall Accuracy: 0.0085
  • Accuracy Background: nan
  • Accuracy Hat: 0.0
  • Accuracy Hair: 0.0000
  • Accuracy Sunglasses: 0.0
  • Accuracy Upper-clothes: 0.0310
  • Accuracy Skirt: 0.0
  • Accuracy Pants: 0.0035
  • Accuracy Dress: 0.0
  • Accuracy Belt: 0.0
  • Accuracy Left-shoe: 0.0
  • Accuracy Right-shoe: 0.0
  • Accuracy Face: 0.0
  • Accuracy Left-leg: 0.0
  • Accuracy Right-leg: 0.0
  • Accuracy Left-arm: 0.0
  • Accuracy Right-arm: 0.0
  • Accuracy Bag: 0.0
  • Accuracy Scarf: 0.0
  • Iou Background: 0.0
  • Iou Hat: 0.0
  • Iou Hair: 0.0000
  • Iou Sunglasses: 0.0
  • Iou Upper-clothes: 0.0296
  • Iou Skirt: 0.0
  • Iou Pants: 0.0035
  • Iou Dress: 0.0
  • Iou Belt: 0.0
  • Iou Left-shoe: 0.0
  • Iou Right-shoe: 0.0
  • Iou Face: 0.0
  • Iou Left-leg: 0.0
  • Iou Right-leg: 0.0
  • Iou Left-arm: 0.0
  • Iou Right-arm: 0.0
  • Iou Bag: 0.0
  • Iou Scarf: 0.0

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: 6e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • 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: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Accuracy Background Accuracy Hat Accuracy Hair Accuracy Sunglasses Accuracy Upper-clothes Accuracy Skirt Accuracy Pants Accuracy Dress Accuracy Belt Accuracy Left-shoe Accuracy Right-shoe Accuracy Face Accuracy Left-leg Accuracy Right-leg Accuracy Left-arm Accuracy Right-arm Accuracy Bag Accuracy Scarf Iou Background Iou Hat Iou Hair Iou Sunglasses Iou Upper-clothes Iou Skirt Iou Pants Iou Dress Iou Belt Iou Left-shoe Iou Right-shoe Iou Face Iou Left-leg Iou Right-leg Iou Left-arm Iou Right-arm Iou Bag Iou Scarf
2.5925 0.2 20 2.5280 0.0127 0.0225 0.0277 nan 0.0047 0.0006 0.0021 0.0074 0.0005 0.1306 0.0226 0.0502 0.0157 0.0016 0.0070 0.0623 0.0000 0.0208 0.0000 0.0520 0.0046 0.0 0.0022 0.0006 0.0003 0.0073 0.0005 0.0846 0.0192 0.0106 0.0100 0.0015 0.0061 0.0369 0.0000 0.0162 0.0000 0.0292 0.0029
2.4147 0.4 40 2.2395 0.0165 0.0295 0.0465 nan 0.0044 0.0008 0.0026 0.0687 0.0012 0.1286 0.0363 0.0591 0.0253 0.0011 0.0112 0.1105 0.0001 0.0102 0.0001 0.0342 0.0066 0.0 0.0027 0.0008 0.0006 0.0553 0.0012 0.0852 0.0286 0.0099 0.0134 0.0010 0.0106 0.0553 0.0001 0.0092 0.0001 0.0193 0.0044
2.2448 0.6 60 2.0775 0.0134 0.0239 0.0646 nan 0.0055 0.0003 0.0043 0.2136 0.0002 0.0212 0.0277 0.0499 0.0153 0.0006 0.0055 0.0462 0.0000 0.0022 0.0001 0.0140 0.0006 0.0 0.0040 0.0003 0.0013 0.1263 0.0002 0.0195 0.0228 0.0087 0.0094 0.0006 0.0054 0.0310 0.0000 0.0021 0.0001 0.0090 0.0006
1.9971 0.8 80 1.9760 0.0122 0.0216 0.0693 nan 0.0038 0.0001 0.0037 0.2462 0.0000 0.0036 0.0223 0.0283 0.0023 0.0004 0.0037 0.0473 0.0 0.0004 0.0001 0.0044 0.0000 0.0 0.0031 0.0001 0.0020 0.1384 0.0000 0.0036 0.0194 0.0092 0.0020 0.0004 0.0036 0.0334 0.0 0.0004 0.0001 0.0036 0.0000
2.0283 1.0 100 1.8169 0.0089 0.0137 0.0471 nan 0.0002 0.0001 0.0024 0.1691 0.0000 0.0018 0.0120 0.0079 0.0002 0.0002 0.0006 0.0374 0.0 0.0001 0.0 0.0010 0.0006 0.0 0.0002 0.0001 0.0021 0.1084 0.0000 0.0018 0.0110 0.0051 0.0002 0.0002 0.0006 0.0299 0.0 0.0001 0.0 0.0009 0.0006
1.8971 1.2 120 1.6797 0.0062 0.0083 0.0305 nan 0.0 0.0000 0.0000 0.1115 0.0000 0.0012 0.0054 0.0017 0.0 0.0 0.0002 0.0201 0.0 0.0 0.0 0.0002 0.0001 0.0 0.0 0.0000 0.0000 0.0846 0.0000 0.0012 0.0052 0.0014 0.0 0.0 0.0002 0.0181 0.0 0.0 0.0 0.0002 0.0001
1.6367 1.4 140 1.5883 0.0045 0.0056 0.0201 nan 0.0 0.0000 0.0 0.0730 0.0001 0.0009 0.0019 0.0018 0.0 0.0 0.0000 0.0174 0.0 0.0 0.0 0.0001 0.0 0.0 0.0 0.0000 0.0 0.0600 0.0001 0.0009 0.0019 0.0018 0.0 0.0 0.0000 0.0162 0.0 0.0 0.0 0.0001 0.0
1.6416 1.6 160 1.4685 0.0023 0.0027 0.0115 nan 0.0 0.0 0.0 0.0434 0.0000 0.0015 0.0002 0.0 0.0 0.0 0.0 0.0008 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0391 0.0000 0.0015 0.0002 0.0 0.0 0.0 0.0 0.0008 0.0 0.0 0.0 0.0 0.0
1.3599 1.8 180 1.3463 0.0012 0.0014 0.0058 nan 0.0 0.0 0.0 0.0224 0.0 0.0001 0.0000 0.0 0.0 0.0 0.0 0.0009 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0214 0.0 0.0001 0.0000 0.0 0.0 0.0 0.0 0.0009 0.0 0.0 0.0 0.0 0.0
1.2645 2.0 200 1.2452 0.0012 0.0013 0.0058 nan 0.0 0.0 0.0 0.0226 0.0 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0216 0.0 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.3066 2.2 220 1.2440 0.0004 0.0004 0.0018 nan 0.0 0.0 0.0 0.0069 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0068 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.3865 2.4 240 1.1572 0.0008 0.0009 0.0040 nan 0.0 0.0 0.0 0.0156 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0152 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.1022 2.6 260 1.0784 0.0004 0.0004 0.0018 nan 0.0 0.0 0.0 0.0068 0.0 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0068 0.0 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.1619 2.8 280 1.0235 0.0005 0.0005 0.0020 nan 0.0 0.0 0.0 0.0075 0.0 0.0009 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0074 0.0 0.0009 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9975 3.0 300 0.9966 0.0007 0.0008 0.0033 nan 0.0 0.0 0.0 0.0128 0.0 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0125 0.0 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.109 3.2 320 1.1302 0.0003 0.0003 0.0012 nan 0.0 0.0 0.0 0.0046 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0045 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.2727 3.4 340 0.9732 0.0002 0.0002 0.0010 nan 0.0 0.0 0.0 0.0034 0.0 0.0007 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0034 0.0 0.0007 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.0256 3.6 360 0.9895 0.0002 0.0002 0.0004 nan 0.0 0.0 0.0 0.0007 0.0 0.0020 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0007 0.0 0.0020 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.0301 3.8 380 0.9926 0.0001 0.0001 0.0003 nan 0.0 0.0 0.0 0.0012 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0011 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.132 4.0 400 0.9476 0.0000 0.0000 0.0001 nan 0.0 0.0 0.0 0.0004 0.0 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0004 0.0 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.977 4.2 420 0.9754 0.0000 0.0000 0.0002 nan 0.0 0.0 0.0 0.0007 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0007 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.014 4.4 440 1.0058 0.0000 0.0000 0.0001 nan 0.0 0.0 0.0 0.0004 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0004 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9142 4.6 460 0.9195 0.0002 0.0002 0.0008 nan 0.0 0.0 0.0 0.0031 0.0 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0030 0.0 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9862 4.8 480 0.9151 0.0001 0.0001 0.0003 nan 0.0 0.0 0.0 0.0011 0.0 0.0 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0011 0.0 0.0 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.0653 5.0 500 0.9210 0.0000 0.0000 0.0002 nan 0.0 0.0 0.0 0.0006 0.0 0.0002 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0006 0.0 0.0002 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.0018 5.2 520 0.9240 0.0000 0.0000 0.0002 nan 0.0 0.0 0.0 0.0008 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0008 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9886 5.4 540 0.8979 0.0000 0.0000 0.0000 nan 0.0 0.0 0.0 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.0629 5.6 560 0.8966 0.0001 0.0001 0.0003 nan 0.0 0.0 0.0 0.0010 0.0 0.0003 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0010 0.0 0.0003 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9999 5.8 580 0.9659 0.0002 0.0002 0.0010 nan 0.0 0.0 0.0 0.0038 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0037 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9133 6.0 600 0.8982 0.0000 0.0000 0.0001 nan 0.0 0.0 0.0 0.0003 0.0 0.0002 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0003 0.0 0.0002 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9606 6.2 620 0.8857 0.0001 0.0001 0.0003 nan 0.0 0.0 0.0 0.0012 0.0 0.0000 0.0003 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0012 0.0 0.0000 0.0003 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9236 6.4 640 0.9046 0.0001 0.0001 0.0004 nan 0.0 0.0 0.0 0.0012 0.0 0.0006 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0012 0.0 0.0006 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.0515 6.6 660 0.8763 0.0006 0.0007 0.0019 nan 0.0 0.0 0.0 0.0038 0.0 0.0075 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0037 0.0 0.0072 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9574 6.8 680 0.8965 0.0000 0.0000 0.0002 nan 0.0 0.0 0.0 0.0007 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0007 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.041 7.0 700 0.9657 0.0000 0.0000 0.0000 nan 0.0 0.0 0.0 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9707 7.2 720 0.8634 0.0001 0.0001 0.0003 nan 0.0 0.0 0.0 0.0011 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0011 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9665 7.4 740 0.8859 0.0000 0.0000 0.0001 nan 0.0 0.0 0.0 0.0005 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0005 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.8678 7.6 760 0.9154 0.0001 0.0001 0.0003 nan 0.0 0.0 0.0 0.0010 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0010 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9318 7.8 780 0.8559 0.0000 0.0000 0.0001 nan 0.0 0.0 0.0 0.0002 0.0 0.0003 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0002 0.0 0.0003 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9266 8.0 800 0.8632 0.0000 0.0000 0.0001 nan 0.0 0.0 0.0 0.0003 0.0 0.0004 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0003 0.0 0.0004 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.8941 8.2 820 0.8701 0.0001 0.0001 0.0003 nan 0.0 0.0 0.0 0.0010 0.0 0.0003 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0010 0.0 0.0003 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.0024 8.4 840 0.8676 0.0002 0.0003 0.0011 nan 0.0 0.0 0.0 0.0039 0.0 0.0006 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0038 0.0 0.0006 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1.0425 8.6 860 0.8907 0.0000 0.0000 0.0000 nan 0.0 0.0 0.0 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9227 8.8 880 0.8380 0.0000 0.0000 0.0000 nan 0.0 0.0 0.0 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9899 9.0 900 0.8837 0.0001 0.0001 0.0005 nan 0.0 0.0 0.0 0.0020 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0020 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9541 9.2 920 0.8495 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.8485 9.4 940 0.8505 0.0001 0.0001 0.0004 nan 0.0 0.0 0.0 0.0014 0.0 0.0003 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0014 0.0 0.0003 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9125 9.6 960 0.8439 0.0013 0.0014 0.0046 nan 0.0 0.0 0.0 0.0123 0.0 0.0115 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0121 0.0 0.0109 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.8274 9.8 980 0.8360 0.0002 0.0002 0.0007 nan 0.0 0.0 0.0 0.0027 0.0 0.0002 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0027 0.0 0.0002 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9485 10.0 1000 0.8360 0.0002 0.0002 0.0007 nan 0.0 0.0 0.0 0.0026 0.0 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0026 0.0 0.0001 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.8216 10.2 1020 0.8169 0.0000 0.0000 0.0001 nan 0.0 0.0 0.0 0.0002 0.0 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0002 0.0 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9409 10.4 1040 0.8487 0.0 0.0 0.0 nan 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.831 10.6 1060 0.8201 0.0000 0.0000 0.0001 nan 0.0 0.0 0.0 0.0004 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0004 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9281 10.8 1080 0.8257 0.0003 0.0003 0.0012 nan 0.0 0.0 0.0 0.0048 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0048 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.8516 11.0 1100 0.8160 0.0004 0.0005 0.0020 nan 0.0 0.0 0.0 0.0077 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0076 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
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0.9182 18.8 1880 0.7412 0.0020 0.0022 0.0094 nan 0.0 0.0 0.0 0.0347 0.0 0.0032 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0330 0.0 0.0031 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9472 19.0 1900 0.7435 0.0017 0.0018 0.0079 nan 0.0 0.0 0.0 0.0299 0.0 0.0015 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0286 0.0 0.0015 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9039 19.2 1920 0.7423 0.0019 0.0022 0.0092 nan 0.0 0.0 0.0 0.0344 0.0 0.0022 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0328 0.0 0.0021 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.7494 19.4 1940 0.7434 0.0016 0.0017 0.0074 nan 0.0 0.0 0.0 0.0279 0.0 0.0016 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0268 0.0 0.0016 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.8478 19.6 1960 0.7417 0.0019 0.0021 0.0090 nan 0.0 0.0 0.0 0.0337 0.0 0.0020 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0321 0.0 0.0020 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.8374 19.8 1980 0.7406 0.0020 0.0022 0.0093 nan 0.0 0.0000 0.0 0.0345 0.0 0.0028 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0000 0.0 0.0328 0.0 0.0028 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.9255 20.0 2000 0.7383 0.0018 0.0020 0.0085 nan 0.0 0.0000 0.0 0.0310 0.0 0.0035 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0000 0.0 0.0296 0.0 0.0035 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.20.3
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Evaluation results

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