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mit-b0-finetuned-contrails-morethanx35newercontrailsdataset

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TensorFlow
segformer
generated_from_keras_callback
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mit-b0-finetuned-contrails-morethanx35newercontrailsdataset / README.md
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metadata
license: other
base_model: nvidia/mit-b0
tags:
  - generated_from_keras_callback
model-index:
  - name: greathero/mit-b0-finetuned-contrails-morethanx35newercontrailsdataset
    results: []

greathero/mit-b0-finetuned-contrails-morethanx35newercontrailsdataset

This model is a fine-tuned version of nvidia/mit-b0 on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.0016
  • Validation Loss: 0.0026
  • Validation Mean Iou: 0.9068
  • Validation Mean Accuracy: 0.9377
  • Validation Overall Accuracy: 0.9993
  • Validation Accuracy Unlabeled: 1.0
  • Validation Accuracy Notlabeled: 0.9997
  • Validation Accuracy Otherclass: 1.0
  • Validation Accuracy Contrail: 0.7513
  • Validation Iou Unlabeled: 1.0
  • Validation Iou Notlabeled: 0.9993
  • Validation Iou Otherclass: 0.9993
  • Validation Iou Contrail: 0.6286
  • Epoch: 49

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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 6e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Validation Loss Validation Mean Iou Validation Mean Accuracy Validation Overall Accuracy Validation Accuracy Unlabeled Validation Accuracy Notlabeled Validation Accuracy Otherclass Validation Accuracy Contrail Validation Iou Unlabeled Validation Iou Notlabeled Validation Iou Otherclass Validation Iou Contrail Epoch
0.2395 0.0367 0.2496 0.25 0.9983 0.0 1.0 0.0 0.0 0.0 0.9983 0.0 0.0 0
0.0286 0.0204 0.2496 0.25 0.9983 0.0 1.0 0.0 0.0 0.0 0.9983 0.0 0.0 1
0.0194 0.0156 0.2496 0.25 0.9983 0.0 1.0 0.0 0.0 0.0 0.9983 0.0 0.0 2
0.0157 0.0144 0.2496 0.25 0.9983 0.0 1.0 0.0 0.0 0.0 0.9983 0.0 0.0 3
0.0141 0.0137 0.2496 0.25 0.9983 0.0 1.0 0.0 0.0 0.0 0.9983 0.0 0.0 4
0.0133 0.0132 0.2496 0.25 0.9983 0.0 1.0 0.0 0.0 0.0 0.9983 0.0 0.0 5
0.0126 0.0125 0.2496 0.25 0.9983 0.0 1.0 0.0 0.0 0.0 0.9983 0.0 0.0 6
0.0118 0.0117 0.2496 0.25 0.9983 0.0 1.0 0.0 0.0 0.0 0.9983 0.0 0.0 7
0.0112 0.0110 0.2551 0.2555 0.9983 0.0 1.0000 0.0222 0.0 0.0 0.9983 0.0220 0.0 8
0.0106 0.0103 0.2744 0.2756 0.9983 0.0180 1.0000 0.0832 0.0013 0.0179 0.9983 0.0801 0.0013 9
0.0100 0.0094 0.3172 0.3225 0.9983 0.0527 1.0000 0.2344 0.0030 0.0521 0.9983 0.2154 0.0030 10
0.0091 0.0087 0.3117 0.3138 0.9983 0.1026 1.0000 0.1470 0.0055 0.1014 0.9983 0.1415 0.0055 11
0.0083 0.0076 0.3844 0.3941 0.9983 0.1540 1.0000 0.4189 0.0037 0.1516 0.9983 0.3840 0.0037 12
0.0073 0.0070 0.4402 0.4781 0.9983 0.1997 0.9999 0.6616 0.0511 0.1978 0.9983 0.5167 0.0479 13
0.0067 0.0062 0.5049 0.5454 0.9983 0.4868 1.0000 0.6893 0.0057 0.4702 0.9983 0.5456 0.0056 14
0.0060 0.0056 0.5133 0.5326 0.9983 0.4799 1.0000 0.6283 0.0221 0.4722 0.9983 0.5608 0.0218 15
0.0055 0.0056 0.5975 0.6504 0.9984 0.7018 0.9999 0.8058 0.0942 0.6731 0.9984 0.6317 0.0868 16
0.0051 0.0050 0.5800 0.6003 0.9984 0.6893 0.9999 0.6644 0.0476 0.6707 0.9984 0.6048 0.0462 17
0.0048 0.0047 0.6598 0.6878 0.9984 0.8252 0.9998 0.7809 0.1453 0.8013 0.9984 0.7095 0.1298 18
0.0045 0.0045 0.6596 0.7122 0.9984 0.9057 0.9998 0.7739 0.1693 0.8117 0.9984 0.6774 0.1508 19
0.0042 0.0042 0.6956 0.7259 0.9985 0.8669 0.9998 0.8294 0.2074 0.8609 0.9985 0.7396 0.1835 20
0.0039 0.0045 0.6824 0.6971 0.9985 0.8710 0.9999 0.7933 0.1243 0.8579 0.9985 0.7546 0.1186 21
0.0038 0.0041 0.7516 0.7748 0.9985 0.9612 0.9998 0.8779 0.2605 0.9397 0.9985 0.8395 0.2287 22
0.0035 0.0038 0.7683 0.8089 0.9986 0.9667 0.9997 0.9334 0.3359 0.9356 0.9986 0.8546 0.2843 23
0.0034 0.0037 0.7905 0.8212 0.9986 0.9639 0.9996 0.9182 0.4031 0.9508 0.9986 0.8856 0.3270 24
0.0032 0.0037 0.7938 0.8154 0.9987 0.9515 0.9997 0.9112 0.3992 0.9469 0.9987 0.8939 0.3358 25
0.0031 0.0036 0.8250 0.8524 0.9988 0.9806 0.9996 0.9431 0.4864 0.9772 0.9988 0.9315 0.3924 26
0.0030 0.0035 0.8204 0.8392 0.9987 0.9736 0.9997 0.9820 0.4015 0.9736 0.9987 0.9659 0.3435 27
0.0029 0.0033 0.8431 0.8689 0.9988 0.9917 0.9997 0.9834 0.5011 0.9910 0.9988 0.9653 0.4172 28
0.0027 0.0034 0.8337 0.8539 0.9988 0.9945 0.9997 0.9875 0.4341 0.9945 0.9988 0.9648 0.3767 29
0.0027 0.0033 0.8518 0.8834 0.9988 1.0 0.9996 0.9931 0.5411 0.9972 0.9988 0.9802 0.4311 30
0.0025 0.0031 0.8622 0.8848 0.9990 0.9986 0.9997 0.9958 0.5449 0.9986 0.9990 0.9890 0.4622 31
0.0025 0.0031 0.8667 0.8975 0.9989 0.9986 0.9996 0.9986 0.5933 0.9979 0.9989 0.9897 0.4801 32
0.0024 0.0031 0.8607 0.8791 0.9990 1.0 0.9998 0.9986 0.5181 1.0 0.9990 0.9877 0.4563 33
0.0022 0.0031 0.8783 0.9102 0.9990 1.0 0.9996 0.9917 0.6497 1.0 0.9990 0.9876 0.5266 34
0.0022 0.0029 0.8780 0.9016 0.9991 1.0 0.9997 0.9931 0.6138 1.0 0.9991 0.9903 0.5225 35
0.0022 0.0030 0.8853 0.9238 0.9991 1.0 0.9996 0.9986 0.6969 0.9972 0.9991 0.9965 0.5484 36
0.0021 0.0030 0.8859 0.9156 0.9991 1.0 0.9996 0.9986 0.6641 1.0 0.9991 0.9979 0.5466 37
0.0021 0.0029 0.8865 0.9165 0.9991 1.0 0.9997 1.0 0.6662 0.9993 0.9991 0.9952 0.5526 38
0.0021 0.0028 0.8932 0.9227 0.9992 1.0 0.9997 0.9986 0.6926 1.0 0.9992 0.9965 0.5771 39
0.0020 0.0029 0.8929 0.9235 0.9992 1.0 0.9997 0.9986 0.6959 1.0 0.9992 0.9979 0.5747 40
0.0020 0.0028 0.8935 0.9252 0.9992 1.0 0.9996 0.9986 0.7026 1.0 0.9991 0.9979 0.5767 41
0.0019 0.0028 0.8934 0.9144 0.9992 1.0 0.9998 0.9986 0.6590 1.0 0.9992 0.9986 0.5758 42
0.0019 0.0028 0.8945 0.9174 0.9992 1.0 0.9997 0.9986 0.6713 1.0 0.9992 0.9979 0.5807 43
0.0018 0.0027 0.9009 0.9327 0.9992 1.0 0.9997 0.9986 0.7324 1.0 0.9992 0.9979 0.6065 44
0.0019 0.0027 0.9028 0.9385 0.9992 1.0 0.9996 1.0 0.7543 1.0 0.9992 0.9993 0.6125 45
0.0017 0.0028 0.9048 0.9362 0.9992 1.0 0.9997 1.0 0.7453 1.0 0.9992 1.0 0.6199 46
0.0017 0.0029 0.9043 0.9362 0.9992 1.0 0.9997 0.9986 0.7466 1.0 0.9992 0.9979 0.6202 47
0.0017 0.0027 0.9060 0.9365 0.9993 1.0 0.9997 0.9986 0.7477 1.0 0.9993 0.9979 0.6270 48
0.0016 0.0026 0.9068 0.9377 0.9993 1.0 0.9997 1.0 0.7513 1.0 0.9993 0.9993 0.6286 49

Framework versions

  • Transformers 4.35.2
  • TensorFlow 2.15.0
  • Datasets 2.15.0
  • Tokenizers 0.15.0