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PushkarA07
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segformer-b0-finetuned-breastcancer-oct-1

Image Segmentation
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  1. README.md +29 -29
  2. model.safetensors +1 -1
  3. runs/Oct01_09-07-39_085488a1e323/events.out.tfevents.1727773828.085488a1e323.1115.1 +3 -0
  4. runs/Oct01_09-07-39_085488a1e323/events.out.tfevents.1727773921.085488a1e323.1115.2 +3 -0
  5. runs/Oct01_09-07-39_085488a1e323/events.out.tfevents.1727774227.085488a1e323.1115.3 +3 -0
  6. runs/Oct01_09-07-39_085488a1e323/events.out.tfevents.1727774293.085488a1e323.1115.4 +3 -0
  7. training_args.bin +1 -1
README.md CHANGED
@@ -1,7 +1,7 @@
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  ---
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- base_model: nvidia/mit-b0
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  library_name: transformers
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  license: other
 
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  tags:
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  - vision
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  - image-segmentation
@@ -18,18 +18,18 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the as-cle-bert/breastcancer-semantic-segmentation dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4728
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- - Mean Iou: 0.3187
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- - Mean Accuracy: 0.4465
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- - Overall Accuracy: 0.9385
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- - Accuracy Ignore: nan
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- - Accuracy Benign Breast Cancer: 0.0
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- - Accuracy Malignant Breast Cancer: 0.3489
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- - Accuracy Background: 0.9906
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- - Iou Ignore: 0.0
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- - Iou Benign Breast Cancer: 0.0
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- - Iou Malignant Breast Cancer: 0.3338
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- - Iou Background: 0.9412
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  ## Model description
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@@ -60,22 +60,22 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Ignore | Accuracy Benign Breast Cancer | Accuracy Malignant Breast Cancer | Accuracy Background | Iou Ignore | Iou Benign Breast Cancer | Iou Malignant Breast Cancer | Iou Background |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:---------------:|:-----------------------------:|:--------------------------------:|:-------------------:|:----------:|:------------------------:|:---------------------------:|:--------------:|
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- | 1.1385 | 0.625 | 10 | 1.2920 | 0.2845 | 0.6989 | 0.8518 | nan | 0.8653 | 0.3362 | 0.8953 | 0.0 | 0.0204 | 0.2461 | 0.8714 |
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- | 1.0733 | 1.25 | 20 | 1.1383 | 0.2877 | 0.4681 | 0.8785 | nan | 0.1718 | 0.3038 | 0.9287 | 0.0 | 0.0050 | 0.2442 | 0.9017 |
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- | 0.9911 | 1.875 | 30 | 0.9850 | 0.3005 | 0.6236 | 0.8853 | nan | 0.5131 | 0.4335 | 0.9243 | 0.0 | 0.0242 | 0.2787 | 0.8990 |
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- | 0.9285 | 2.5 | 40 | 0.7954 | 0.3396 | 0.6975 | 0.9164 | nan | 0.6465 | 0.4931 | 0.9527 | 0.0 | 0.0906 | 0.3522 | 0.9156 |
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- | 0.7114 | 3.125 | 50 | 0.6539 | 0.3229 | 0.5058 | 0.9292 | nan | 0.1553 | 0.3852 | 0.9770 | 0.0 | 0.0249 | 0.3372 | 0.9296 |
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- | 0.725 | 3.75 | 60 | 0.5886 | 0.3291 | 0.4826 | 0.9261 | nan | 0.0 | 0.4822 | 0.9658 | 0.0 | 0.0 | 0.3890 | 0.9272 |
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- | 0.7755 | 4.375 | 70 | 0.5801 | 0.3060 | 0.4322 | 0.9225 | nan | 0.0 | 0.3210 | 0.9755 | 0.0 | 0.0 | 0.2909 | 0.9331 |
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- | 0.5846 | 5.0 | 80 | 0.6225 | 0.2787 | 0.4098 | 0.9204 | nan | 0.0624 | 0.1822 | 0.9848 | 0.0 | 0.0049 | 0.1761 | 0.9340 |
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- | 0.5753 | 5.625 | 90 | 0.5340 | 0.3242 | 0.4586 | 0.9365 | nan | 0.0 | 0.3909 | 0.9848 | 0.0 | 0.0 | 0.3568 | 0.9401 |
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- | 0.5912 | 6.25 | 100 | 0.5389 | 0.3212 | 0.4580 | 0.9352 | nan | 0.0 | 0.3907 | 0.9834 | 0.0 | 0.0 | 0.3478 | 0.9368 |
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- | 0.5518 | 6.875 | 110 | 0.5188 | 0.3151 | 0.4470 | 0.9340 | nan | 0.0 | 0.3558 | 0.9851 | 0.0 | 0.0 | 0.3230 | 0.9373 |
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- | 0.4876 | 7.5 | 120 | 0.5076 | 0.3452 | 0.4905 | 0.9435 | nan | 0.0 | 0.4873 | 0.9843 | 0.0 | 0.0 | 0.4360 | 0.9450 |
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- | 0.5017 | 8.125 | 130 | 0.4774 | 0.3104 | 0.4356 | 0.9351 | nan | 0.0009 | 0.3164 | 0.9896 | 0.0 | 0.0001 | 0.3023 | 0.9391 |
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- | 0.4706 | 8.75 | 140 | 0.4785 | 0.3149 | 0.4514 | 0.9357 | nan | 0.0349 | 0.3304 | 0.9889 | 0.0 | 0.0057 | 0.3153 | 0.9388 |
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- | 0.5787 | 9.375 | 150 | 0.4723 | 0.3203 | 0.4492 | 0.9390 | nan | 0.0 | 0.3571 | 0.9904 | 0.0 | 0.0 | 0.3402 | 0.9411 |
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- | 0.5399 | 10.0 | 160 | 0.4728 | 0.3187 | 0.4465 | 0.9385 | nan | 0.0 | 0.3489 | 0.9906 | 0.0 | 0.0 | 0.3338 | 0.9412 |
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80
 
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  ### Framework versions
 
1
  ---
 
2
  library_name: transformers
3
  license: other
4
+ base_model: nvidia/mit-b0
5
  tags:
6
  - vision
7
  - image-segmentation
 
18
 
19
  This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the as-cle-bert/breastcancer-semantic-segmentation dataset.
20
  It achieves the following results on the evaluation set:
21
+ - Loss: 0.2413
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+ - Mean Iou: 0.4091
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+ - Mean Accuracy: 0.5395
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+ - Overall Accuracy: 0.9467
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+ - Accuracy Ignore: 0.1246
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+ - Accuracy Benign Breast Cancer: 0.5579
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+ - Accuracy Malignant Breast Cancer: 0.4873
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+ - Accuracy Background: 0.9882
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+ - Iou Ignore: 0.1150
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+ - Iou Benign Breast Cancer: 0.1215
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+ - Iou Malignant Breast Cancer: 0.4523
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+ - Iou Background: 0.9478
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  ## Model description
35
 
 
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61
  | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Ignore | Accuracy Benign Breast Cancer | Accuracy Malignant Breast Cancer | Accuracy Background | Iou Ignore | Iou Benign Breast Cancer | Iou Malignant Breast Cancer | Iou Background |
62
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:---------------:|:-----------------------------:|:--------------------------------:|:-------------------:|:----------:|:------------------------:|:---------------------------:|:--------------:|
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+ | 0.074 | 0.625 | 10 | 0.2831 | 0.3265 | 0.5114 | 0.9244 | 0.0 | 0.7065 | 0.3650 | 0.9742 | 0.0 | 0.0562 | 0.3140 | 0.9359 |
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+ | 0.0747 | 1.25 | 20 | 0.2687 | 0.3706 | 0.4979 | 0.9394 | 0.0 | 0.5673 | 0.4396 | 0.9846 | 0.0 | 0.1507 | 0.3934 | 0.9382 |
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+ | 0.1038 | 1.875 | 30 | 0.2365 | 0.3962 | 0.5469 | 0.9464 | 0.0206 | 0.6556 | 0.5268 | 0.9845 | 0.0205 | 0.1487 | 0.4688 | 0.9469 |
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+ | 0.0884 | 2.5 | 40 | 0.2424 | 0.3985 | 0.5438 | 0.9450 | 0.0784 | 0.6292 | 0.4807 | 0.9869 | 0.0752 | 0.1318 | 0.4410 | 0.9461 |
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+ | 0.0591 | 3.125 | 50 | 0.2473 | 0.3919 | 0.5478 | 0.9384 | 0.1061 | 0.6262 | 0.4793 | 0.9797 | 0.1006 | 0.1115 | 0.4161 | 0.9393 |
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+ | 0.0566 | 3.75 | 60 | 0.2776 | 0.3640 | 0.4351 | 0.9388 | 0.1037 | 0.2770 | 0.3692 | 0.9904 | 0.0984 | 0.0697 | 0.3485 | 0.9393 |
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+ | 0.063 | 4.375 | 70 | 0.2262 | 0.4058 | 0.5094 | 0.9472 | 0.1072 | 0.4018 | 0.5440 | 0.9844 | 0.1015 | 0.0892 | 0.4848 | 0.9478 |
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+ | 0.0358 | 5.0 | 80 | 0.2398 | 0.4065 | 0.5087 | 0.9464 | 0.1084 | 0.4191 | 0.5220 | 0.9854 | 0.1026 | 0.1078 | 0.4699 | 0.9457 |
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+ | 0.0319 | 5.625 | 90 | 0.2659 | 0.3844 | 0.4737 | 0.9423 | 0.1103 | 0.3823 | 0.4122 | 0.9902 | 0.1034 | 0.1010 | 0.3917 | 0.9416 |
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+ | 0.0499 | 6.25 | 100 | 0.2393 | 0.4030 | 0.5532 | 0.9423 | 0.1065 | 0.6272 | 0.4963 | 0.9826 | 0.1006 | 0.1285 | 0.4407 | 0.9423 |
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+ | 0.0394 | 6.875 | 110 | 0.2415 | 0.4024 | 0.5233 | 0.9463 | 0.1086 | 0.5205 | 0.4751 | 0.9890 | 0.1026 | 0.1137 | 0.4464 | 0.9470 |
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+ | 0.037 | 7.5 | 120 | 0.2475 | 0.3916 | 0.4752 | 0.9458 | 0.1124 | 0.3507 | 0.4465 | 0.9912 | 0.1053 | 0.0904 | 0.4245 | 0.9462 |
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+ | 0.0588 | 8.125 | 130 | 0.2458 | 0.4041 | 0.5223 | 0.9455 | 0.1276 | 0.5146 | 0.4577 | 0.9895 | 0.1171 | 0.1240 | 0.4292 | 0.9460 |
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+ | 0.0426 | 8.75 | 140 | 0.2463 | 0.4046 | 0.5264 | 0.9459 | 0.1225 | 0.5322 | 0.4614 | 0.9897 | 0.1134 | 0.1252 | 0.4333 | 0.9467 |
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+ | 0.0848 | 9.375 | 150 | 0.2388 | 0.4078 | 0.5297 | 0.9469 | 0.1154 | 0.5298 | 0.4849 | 0.9888 | 0.1078 | 0.1253 | 0.4506 | 0.9475 |
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+ | 0.0574 | 10.0 | 160 | 0.2413 | 0.4091 | 0.5395 | 0.9467 | 0.1246 | 0.5579 | 0.4873 | 0.9882 | 0.1150 | 0.1215 | 0.4523 | 0.9478 |
79
 
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  ### Framework versions
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