File size: 8,587 Bytes
989823e e3048b4 989823e e3048b4 aae2cfa 2085d98 27fa54c 2085d98 e3048b4 83bcd2c e3048b4 fbf44e9 4099131 21f2b08 e60ea41 717a6f0 f4096b3 8669279 218a98e faf9056 3f46e12 4bceb24 af61c0a 84bd068 87e04ff 7c9ecac 11163fa 2360ca9 bf7e636 a8dc03e 3aad26c 8709491 618fb68 93ff89e d8b0ac4 a658f87 a4536d6 a952da6 ae56c5c fe48589 81d5f09 5f18301 c1b8edc 8faadbf cf344fc b5bacaa 0be2e99 a411e4f ebce84c b0b2467 28fa1e2 4342be5 204b7ac b4b99ef 5afbfa7 1a6dea0 363a62e 0b35c12 a43148b 83bcd2c 27fa54c 8569f61 0a0582d 2f498f6 258ce97 acb96f3 aae2cfa 2085d98 e3048b4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 |
---
license: other
tags:
- generated_from_keras_callback
model-index:
- name: AhamadShaik/SegFormer_RESIZE_NLM
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# AhamadShaik/SegFormer_RESIZE_NLM
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0421
- Train Dice Coef: 0.8821
- Train Iou: 0.7909
- Validation Loss: 0.0426
- Validation Dice Coef: 0.8896
- Validation Iou: 0.8023
- Train Lr: 1e-10
- Epoch: 57
## 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:
- optimizer: {'name': 'Adam', 'learning_rate': 1e-10, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Train Dice Coef | Train Iou | Validation Loss | Validation Dice Coef | Validation Iou | Train Lr | Epoch |
|:----------:|:---------------:|:---------:|:---------------:|:--------------------:|:--------------:|:--------:|:-----:|
| 0.2282 | 0.5657 | 0.4102 | 0.1322 | 0.6524 | 0.4967 | 1e-04 | 0 |
| 0.1354 | 0.6853 | 0.5329 | 0.0855 | 0.7853 | 0.6544 | 1e-04 | 1 |
| 0.1105 | 0.7364 | 0.5924 | 0.0737 | 0.8147 | 0.6916 | 1e-04 | 2 |
| 0.0985 | 0.7610 | 0.6226 | 0.0632 | 0.8518 | 0.7440 | 1e-04 | 3 |
| 0.0933 | 0.7745 | 0.6399 | 0.0627 | 0.8455 | 0.7351 | 1e-04 | 4 |
| 0.0886 | 0.7856 | 0.6535 | 0.0584 | 0.8603 | 0.7566 | 1e-04 | 5 |
| 0.0831 | 0.7971 | 0.6695 | 0.0559 | 0.8621 | 0.7596 | 1e-04 | 6 |
| 0.0770 | 0.8107 | 0.6867 | 0.0530 | 0.8726 | 0.7756 | 1e-04 | 7 |
| 0.0741 | 0.8160 | 0.6942 | 0.0512 | 0.8775 | 0.7832 | 1e-04 | 8 |
| 0.0750 | 0.8163 | 0.6945 | 0.0581 | 0.8627 | 0.7606 | 1e-04 | 9 |
| 0.0678 | 0.8306 | 0.7138 | 0.0531 | 0.8719 | 0.7745 | 1e-04 | 10 |
| 0.0659 | 0.8341 | 0.7196 | 0.0519 | 0.8738 | 0.7781 | 1e-04 | 11 |
| 0.0626 | 0.8412 | 0.7294 | 0.0496 | 0.8789 | 0.7853 | 1e-04 | 12 |
| 0.0637 | 0.8383 | 0.7257 | 0.0515 | 0.8772 | 0.7828 | 1e-04 | 13 |
| 0.0601 | 0.8462 | 0.7367 | 0.0498 | 0.8765 | 0.7814 | 1e-04 | 14 |
| 0.0573 | 0.8525 | 0.7458 | 0.0474 | 0.8817 | 0.7897 | 1e-04 | 15 |
| 0.0565 | 0.8520 | 0.7456 | 0.0459 | 0.8850 | 0.7948 | 1e-04 | 16 |
| 0.0633 | 0.8381 | 0.7262 | 0.0487 | 0.8797 | 0.7868 | 1e-04 | 17 |
| 0.0558 | 0.8544 | 0.7489 | 0.0476 | 0.8828 | 0.7917 | 1e-04 | 18 |
| 0.0523 | 0.8617 | 0.7595 | 0.0454 | 0.8872 | 0.7983 | 1e-04 | 19 |
| 0.0516 | 0.8632 | 0.7617 | 0.0465 | 0.8838 | 0.7934 | 1e-04 | 20 |
| 0.0515 | 0.8636 | 0.7625 | 0.0494 | 0.8816 | 0.7894 | 1e-04 | 21 |
| 0.0518 | 0.8630 | 0.7615 | 0.0487 | 0.8836 | 0.7930 | 1e-04 | 22 |
| 0.0521 | 0.8616 | 0.7595 | 0.0483 | 0.8822 | 0.7908 | 1e-04 | 23 |
| 0.0510 | 0.8634 | 0.7624 | 0.0501 | 0.8814 | 0.7899 | 1e-04 | 24 |
| 0.0485 | 0.8703 | 0.7728 | 0.0439 | 0.8892 | 0.8018 | 5e-06 | 25 |
| 0.0464 | 0.8755 | 0.7807 | 0.0433 | 0.8890 | 0.8015 | 5e-06 | 26 |
| 0.0456 | 0.8760 | 0.7817 | 0.0439 | 0.8884 | 0.8004 | 5e-06 | 27 |
| 0.0446 | 0.8790 | 0.7860 | 0.0428 | 0.8896 | 0.8024 | 5e-06 | 28 |
| 0.0443 | 0.8786 | 0.7855 | 0.0426 | 0.8905 | 0.8038 | 5e-06 | 29 |
| 0.0439 | 0.8795 | 0.7867 | 0.0439 | 0.8881 | 0.7999 | 5e-06 | 30 |
| 0.0436 | 0.8800 | 0.7876 | 0.0429 | 0.8902 | 0.8032 | 5e-06 | 31 |
| 0.0430 | 0.8809 | 0.7890 | 0.0439 | 0.8876 | 0.7992 | 5e-06 | 32 |
| 0.0427 | 0.8812 | 0.7894 | 0.0432 | 0.8892 | 0.8016 | 5e-06 | 33 |
| 0.0431 | 0.8798 | 0.7875 | 0.0433 | 0.8895 | 0.8022 | 5e-06 | 34 |
| 0.0425 | 0.8816 | 0.7903 | 0.0435 | 0.8892 | 0.8016 | 2.5e-07 | 35 |
| 0.0420 | 0.8826 | 0.7917 | 0.0433 | 0.8894 | 0.8021 | 2.5e-07 | 36 |
| 0.0423 | 0.8833 | 0.7926 | 0.0429 | 0.8893 | 0.8018 | 2.5e-07 | 37 |
| 0.0420 | 0.8833 | 0.7929 | 0.0430 | 0.8895 | 0.8023 | 2.5e-07 | 38 |
| 0.0424 | 0.8832 | 0.7924 | 0.0437 | 0.8890 | 0.8013 | 2.5e-07 | 39 |
| 0.0422 | 0.8824 | 0.7914 | 0.0427 | 0.8897 | 0.8024 | 1.25e-08 | 40 |
| 0.0426 | 0.8824 | 0.7913 | 0.0431 | 0.8900 | 0.8030 | 1.25e-08 | 41 |
| 0.0424 | 0.8832 | 0.7926 | 0.0433 | 0.8893 | 0.8019 | 1.25e-08 | 42 |
| 0.0424 | 0.8830 | 0.7922 | 0.0436 | 0.8886 | 0.8008 | 1.25e-08 | 43 |
| 0.0427 | 0.8806 | 0.7888 | 0.0434 | 0.8893 | 0.8020 | 1.25e-08 | 44 |
| 0.0421 | 0.8829 | 0.7921 | 0.0431 | 0.8899 | 0.8028 | 6.25e-10 | 45 |
| 0.0427 | 0.8817 | 0.7901 | 0.0431 | 0.8896 | 0.8023 | 6.25e-10 | 46 |
| 0.0422 | 0.8825 | 0.7916 | 0.0433 | 0.8895 | 0.8022 | 6.25e-10 | 47 |
| 0.0423 | 0.8823 | 0.7912 | 0.0431 | 0.8897 | 0.8024 | 6.25e-10 | 48 |
| 0.0423 | 0.8826 | 0.7916 | 0.0433 | 0.8895 | 0.8021 | 6.25e-10 | 49 |
| 0.0425 | 0.8827 | 0.7918 | 0.0433 | 0.8896 | 0.8023 | 1e-10 | 50 |
| 0.0421 | 0.8838 | 0.7937 | 0.0431 | 0.8891 | 0.8014 | 1e-10 | 51 |
| 0.0424 | 0.8820 | 0.7907 | 0.0436 | 0.8884 | 0.8003 | 1e-10 | 52 |
| 0.0424 | 0.8824 | 0.7915 | 0.0426 | 0.8899 | 0.8029 | 1e-10 | 53 |
| 0.0423 | 0.8828 | 0.7920 | 0.0433 | 0.8894 | 0.8020 | 1e-10 | 54 |
| 0.0424 | 0.8818 | 0.7905 | 0.0431 | 0.8901 | 0.8031 | 1e-10 | 55 |
| 0.0421 | 0.8823 | 0.7911 | 0.0438 | 0.8887 | 0.8008 | 1e-10 | 56 |
| 0.0421 | 0.8821 | 0.7909 | 0.0426 | 0.8896 | 0.8023 | 1e-10 | 57 |
### Framework versions
- Transformers 4.27.4
- TensorFlow 2.10.1
- Datasets 2.11.0
- Tokenizers 0.13.3
|