greathero
/

mit-b0-finetuned-contrails-morethanx35newercontrailsdataset

Transformers

TensorFlow

segformer

generated_from_keras_callback

Inference Endpoints

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greathero commited on Jan 1

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1 Parent(s): 3b5f86e

Training in progress epoch 47

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README.md +8 -7
tf_model.h5 +1 -1

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@@ -16,19 +16,19 @@ probably proofread and complete it, then remove this comment. -->
 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: 0.0017
-- Validation Loss: 0.0028
-- Validation Mean Iou: 0.9048
 - Validation Mean Accuracy: 0.9362
 - Validation Overall Accuracy: 0.9992
 - Validation Accuracy Unlabeled: 1.0
 - Validation Accuracy Notlabeled: 0.9997
-- Validation Accuracy Otherclass: 1.0
-- Validation Accuracy Contrail: 0.7453
 - Validation Iou Unlabeled: 1.0
 - Validation Iou Notlabeled: 0.9992
-- Validation Iou Otherclass: 1.0
-- Validation Iou Contrail: 0.6199
-- Epoch: 46
 ## Model description
@@ -101,6 +101,7 @@ The following hyperparameters were used during training:
 | 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    |
 ### Framework versions

 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: 0.0017
+- Validation Loss: 0.0029
+- Validation Mean Iou: 0.9043
 - Validation Mean Accuracy: 0.9362
 - Validation Overall Accuracy: 0.9992
 - Validation Accuracy Unlabeled: 1.0
 - Validation Accuracy Notlabeled: 0.9997
+- Validation Accuracy Otherclass: 0.9986
+- Validation Accuracy Contrail: 0.7466
 - Validation Iou Unlabeled: 1.0
 - Validation Iou Notlabeled: 0.9992
+- Validation Iou Otherclass: 0.9979
+- Validation Iou Contrail: 0.6202
+- Epoch: 47
 ## Model description
 | 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    |
 ### Framework versions

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