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End of training
d7d58c1
metadata
license: apache-2.0
base_model: microsoft/conditional-detr-resnet-50
tags:
  - generated_from_trainer
model-index:
  - name: cdetr-mist1-brain-gt-tumors-8ah-6l
    results: []

cdetr-mist1-brain-gt-tumors-8ah-6l

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

  • Loss: 2.7389

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: 1e-05
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
5.4149 1.0 115 4.3974
3.9453 2.0 230 3.6520
3.7269 3.0 345 3.7602
3.5898 4.0 460 3.5671
3.486 5.0 575 3.4912
3.4073 6.0 690 3.4095
3.4181 7.0 805 3.3183
3.3603 8.0 920 3.1111
3.2777 9.0 1035 3.1992
3.2851 10.0 1150 3.3997
3.266 11.0 1265 3.2861
3.2803 12.0 1380 3.1813
3.1733 13.0 1495 2.9838
3.2094 14.0 1610 3.1175
3.1718 15.0 1725 3.0064
3.1303 16.0 1840 3.0869
3.0897 17.0 1955 3.0306
3.0233 18.0 2070 2.9479
3.0156 19.0 2185 2.9145
3.0277 20.0 2300 2.8919
3.0847 21.0 2415 2.9321
3.0333 22.0 2530 2.9128
3.0126 23.0 2645 2.8627
2.9968 24.0 2760 3.0186
3.0295 25.0 2875 3.0148
3.0294 26.0 2990 3.0341
3.0395 27.0 3105 2.9997
3.0445 28.0 3220 3.0575
2.9761 29.0 3335 2.9707
3.0075 30.0 3450 2.9392
3.0198 31.0 3565 2.9122
2.9782 32.0 3680 2.9471
2.9773 33.0 3795 3.0306
2.9528 34.0 3910 2.8513
2.9228 35.0 4025 2.8997
2.9221 36.0 4140 2.8646
2.8933 37.0 4255 2.8871
2.8925 38.0 4370 2.9407
2.9069 39.0 4485 2.9625
2.9246 40.0 4600 2.9946
2.9089 41.0 4715 2.8936
2.8573 42.0 4830 2.8272
2.8768 43.0 4945 2.9868
2.9666 44.0 5060 2.9200
2.958 45.0 5175 2.8755
2.8923 46.0 5290 2.8518
2.9204 47.0 5405 2.9000
2.9644 48.0 5520 2.8969
2.9011 49.0 5635 2.7918
2.9329 50.0 5750 2.9139
2.9031 51.0 5865 2.7796
2.9029 52.0 5980 2.8025
2.9555 53.0 6095 2.9121
2.9366 54.0 6210 2.9035
2.8871 55.0 6325 2.8759
2.863 56.0 6440 2.8540
2.8897 57.0 6555 2.8401
2.828 58.0 6670 2.8590
2.8221 59.0 6785 2.9255
2.835 60.0 6900 2.9809
2.886 61.0 7015 2.9907
2.8227 62.0 7130 2.8283
2.7864 63.0 7245 2.8258
2.8179 64.0 7360 2.9504
2.7944 65.0 7475 2.8042
2.7986 66.0 7590 2.8307
2.7567 67.0 7705 2.8060
2.7552 68.0 7820 2.7994
2.7933 69.0 7935 2.8493
2.7393 70.0 8050 2.8409
2.7357 71.0 8165 2.8086
2.7264 72.0 8280 2.7773
2.7614 73.0 8395 2.8937
2.7279 74.0 8510 2.8887
2.745 75.0 8625 2.8274
2.7225 76.0 8740 2.7971
2.7094 77.0 8855 2.8685
2.7306 78.0 8970 2.8482
2.6844 79.0 9085 2.7372
2.6949 80.0 9200 2.8149
2.7342 81.0 9315 2.7647
2.6813 82.0 9430 2.7666
2.7161 83.0 9545 2.8437
2.6953 84.0 9660 2.7895
2.6714 85.0 9775 2.7683
2.6611 86.0 9890 2.7004
2.6714 87.0 10005 2.7183
2.6655 88.0 10120 2.7043
2.6509 89.0 10235 2.7705
2.6266 90.0 10350 2.7152
2.6677 91.0 10465 2.7295
2.6438 92.0 10580 2.7018
2.6267 93.0 10695 2.7063
2.6286 94.0 10810 2.7798
2.6043 95.0 10925 2.7712
2.6188 96.0 11040 2.7614
2.6028 97.0 11155 2.7405
2.621 98.0 11270 2.7415
2.61 99.0 11385 2.7415
2.6164 100.0 11500 2.7389

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.14.1