File size: 20,453 Bytes
84f9327 7ac5a94 368cbc6 35e4921 3b5f86e 7ac5a94 6995af1 368cbc6 7ac5a94 84f9327 e115417 127c45d 5a8bcd7 d3a25e1 53a303d c499917 c932fd1 90bcf5e b45f576 9e5d684 8b94945 1161d7e c7aa004 1c298e4 bf820ff 625a1f7 ceb562c 9bda1d2 45fae6e 882ec37 c9950bc 8a0d201 5ca4793 dc1d695 1f34d17 194274e 131e7ce 0f51d92 353c14c 6353da4 c85eac3 fcf0b28 35e4921 2729e52 6e9a17b 8c24d16 7393bfd aabcf0b 6995af1 5aae17b 642e23d 49a11bb 9e9e697 9770227 9333b72 3b5f86e d283ae9 368cbc6 7ac5a94 84f9327 |
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 |
---
license: other
base_model: nvidia/mit-b0
tags:
- generated_from_keras_callback
model-index:
- name: greathero/mit-b0-finetuned-contrails-morethanx35newercontrailsdataset
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. -->
# greathero/mit-b0-finetuned-contrails-morethanx35newercontrailsdataset
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: 0.0016
- 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
|