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detr_finetuned_airdataset

This model is a fine-tuned version of microsoft/conditional-detr-resnet-50 on the dsi dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8959
  • Map: 0.3195
  • Map 50: 0.7784
  • Map 75: 0.1925
  • Map Small: 0.3211
  • Map Medium: 0.0079
  • Map Large: -1.0
  • Mar 1: 0.0256
  • Mar 10: 0.1995
  • Mar 100: 0.487
  • Mar Small: 0.4896
  • Mar Medium: 0.0061
  • Mar Large: -1.0
  • Map Falciparum Trophozoite: 0.3195
  • Mar 100 Falciparum Trophozoite: 0.487
  • Map Wbc: -1.0
  • Mar 100 Wbc: -1.0

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 30

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 Falciparum Trophozoite Mar 100 Falciparum Trophozoite Map Wbc Mar 100 Wbc
No log 1.0 209 1.2206 0.1424 0.401 0.07 0.1429 0.0328 -1.0 0.0168 0.1239 0.4185 0.4204 0.0612 -1.0 0.1424 0.4185 -1.0 -1.0
No log 2.0 418 1.1354 0.2136 0.585 0.1077 0.2145 0.0224 -1.0 0.0212 0.1608 0.4102 0.4123 0.0224 -1.0 0.2136 0.4102 -1.0 -1.0
1.3747 3.0 627 1.0729 0.2353 0.6428 0.1092 0.2365 0.0229 -1.0 0.0216 0.1669 0.4247 0.4268 0.0245 -1.0 0.2353 0.4247 -1.0 -1.0
1.3747 4.0 836 1.0260 0.2548 0.6701 0.1339 0.2563 0.0178 -1.0 0.0234 0.1792 0.4424 0.4447 0.0163 -1.0 0.2548 0.4424 -1.0 -1.0
1.0467 5.0 1045 1.0116 0.2576 0.6811 0.1321 0.2589 0.0208 -1.0 0.0229 0.1773 0.4422 0.4445 0.0184 -1.0 0.2576 0.4422 -1.0 -1.0
1.0467 6.0 1254 1.0150 0.2526 0.6842 0.1191 0.2537 0.0089 -1.0 0.0226 0.1724 0.4463 0.4486 0.0082 -1.0 0.2526 0.4463 -1.0 -1.0
1.0467 7.0 1463 0.9933 0.2627 0.699 0.1376 0.2639 0.0211 -1.0 0.0215 0.1773 0.4458 0.4481 0.0224 -1.0 0.2627 0.4458 -1.0 -1.0
0.9905 8.0 1672 0.9642 0.2797 0.7188 0.1511 0.2809 0.0112 -1.0 0.0241 0.1858 0.459 0.4614 0.0143 -1.0 0.2797 0.459 -1.0 -1.0
0.9905 9.0 1881 0.9641 0.2786 0.7209 0.1453 0.2803 0.0103 -1.0 0.0231 0.1861 0.4534 0.4558 0.0102 -1.0 0.2786 0.4534 -1.0 -1.0
0.955 10.0 2090 0.9869 0.2685 0.7158 0.1366 0.27 0.0023 -1.0 0.0225 0.1789 0.4442 0.4465 0.0041 -1.0 0.2685 0.4442 -1.0 -1.0
0.955 11.0 2299 0.9612 0.2837 0.7238 0.1534 0.2856 0.0067 -1.0 0.0242 0.1878 0.4568 0.4592 0.0082 -1.0 0.2837 0.4568 -1.0 -1.0
0.9248 12.0 2508 0.9437 0.2938 0.7368 0.1635 0.2954 0.005 -1.0 0.0239 0.1882 0.4701 0.4727 0.0041 -1.0 0.2938 0.4701 -1.0 -1.0
0.9248 13.0 2717 0.9390 0.289 0.7371 0.16 0.2903 0.0149 -1.0 0.0254 0.191 0.4685 0.471 0.0122 -1.0 0.289 0.4685 -1.0 -1.0
0.9248 14.0 2926 0.9321 0.2986 0.7428 0.1744 0.3002 0.005 -1.0 0.0251 0.1928 0.4743 0.4768 0.0041 -1.0 0.2986 0.4743 -1.0 -1.0
0.9027 15.0 3135 0.9448 0.2911 0.7418 0.1588 0.2924 0.0139 -1.0 0.0241 0.1877 0.4678 0.4702 0.0122 -1.0 0.2911 0.4678 -1.0 -1.0
0.9027 16.0 3344 0.9259 0.3033 0.7549 0.174 0.3047 0.005 -1.0 0.0249 0.1931 0.4736 0.4762 0.0041 -1.0 0.3033 0.4736 -1.0 -1.0
0.8725 17.0 3553 0.9200 0.3039 0.7554 0.1795 0.3055 0.0069 -1.0 0.0259 0.1949 0.4764 0.479 0.0061 -1.0 0.3039 0.4764 -1.0 -1.0
0.8725 18.0 3762 0.9129 0.3068 0.7622 0.1786 0.3083 0.0089 -1.0 0.026 0.1961 0.4817 0.4842 0.0082 -1.0 0.3068 0.4817 -1.0 -1.0
0.8725 19.0 3971 0.9053 0.3129 0.7699 0.182 0.3146 0.0119 -1.0 0.0253 0.1986 0.4806 0.4832 0.0102 -1.0 0.3129 0.4806 -1.0 -1.0
0.8532 20.0 4180 0.9124 0.3076 0.7661 0.1794 0.3093 0.0069 -1.0 0.0252 0.1972 0.4798 0.4823 0.0061 -1.0 0.3076 0.4798 -1.0 -1.0
0.8532 21.0 4389 0.9060 0.3129 0.7694 0.182 0.3146 0.0139 -1.0 0.0254 0.1988 0.4811 0.4837 0.0122 -1.0 0.3129 0.4811 -1.0 -1.0
0.8362 22.0 4598 0.9007 0.3157 0.7733 0.1886 0.3173 0.0079 -1.0 0.0255 0.2005 0.4834 0.4859 0.0061 -1.0 0.3157 0.4834 -1.0 -1.0
0.8362 23.0 4807 0.9036 0.3148 0.7702 0.1859 0.3159 0.0119 -1.0 0.0255 0.1982 0.4859 0.4884 0.0102 -1.0 0.3148 0.4859 -1.0 -1.0
0.8211 24.0 5016 0.8988 0.3159 0.7733 0.1875 0.3172 0.005 -1.0 0.0253 0.1988 0.4844 0.487 0.0041 -1.0 0.3159 0.4844 -1.0 -1.0
0.8211 25.0 5225 0.8989 0.3175 0.7741 0.1888 0.3189 0.0079 -1.0 0.0256 0.1995 0.486 0.4886 0.0061 -1.0 0.3175 0.486 -1.0 -1.0
0.8211 26.0 5434 0.8980 0.3188 0.776 0.1918 0.3204 0.005 -1.0 0.0258 0.1998 0.4867 0.4893 0.0041 -1.0 0.3188 0.4867 -1.0 -1.0
0.8091 27.0 5643 0.8953 0.3204 0.7786 0.1931 0.3219 0.0079 -1.0 0.026 0.2002 0.4863 0.4889 0.0061 -1.0 0.3204 0.4863 -1.0 -1.0
0.8091 28.0 5852 0.8973 0.3192 0.7784 0.1911 0.3208 0.0079 -1.0 0.0255 0.199 0.4867 0.4892 0.0061 -1.0 0.3192 0.4867 -1.0 -1.0
0.8001 29.0 6061 0.8962 0.3196 0.7785 0.1926 0.3211 0.0079 -1.0 0.0257 0.1994 0.487 0.4896 0.0061 -1.0 0.3196 0.487 -1.0 -1.0
0.8001 30.0 6270 0.8959 0.3195 0.7784 0.1925 0.3211 0.0079 -1.0 0.0256 0.1995 0.487 0.4896 0.0061 -1.0 0.3195 0.487 -1.0 -1.0

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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