Model save

README.md

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+---
+license: other
+base_model: nvidia/mit-b0
+tags:
+- generated_from_trainer
+model-index:
+- name: segformer-finetuned-obb-1k-steps
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# segformer-finetuned-obb-1k-steps
+
+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:
+- Loss: 0.0511
+- Mean Iou: 0.2238
+- Mean Accuracy: 0.4477
+- Overall Accuracy: 0.4477
+- Accuracy  Backgound : nan
+- Accuracy Rwy Obb: 0.4477
+- Iou  Backgound : 0.0
+- Iou Rwy Obb: 0.4477
+
+## 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:
+- learning_rate: 6e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 1337
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: polynomial
+- training_steps: 1000
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy  Backgound  | Accuracy Rwy Obb | Iou  Backgound  | Iou Rwy Obb |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------------:|:----------------:|:---------------:|:-----------:|
+| 0.3927        | 1.0    | 173  | 0.1096          | 0.1590   | 0.3180        | 0.3180           | nan                  | 0.3180           | 0.0             | 0.3180      |
+| 0.0969        | 2.0    | 346  | 0.0704          | 0.2112   | 0.4224        | 0.4224           | nan                  | 0.4224           | 0.0             | 0.4224      |
+| 0.0651        | 3.0    | 519  | 0.0598          | 0.2186   | 0.4371        | 0.4371           | nan                  | 0.4371           | 0.0             | 0.4371      |
+| 0.0576        | 4.0    | 692  | 0.0530          | 0.2250   | 0.4500        | 0.4500           | nan                  | 0.4500           | 0.0             | 0.4500      |
+| 0.0531        | 5.0    | 865  | 0.0529          | 0.2212   | 0.4424        | 0.4424           | nan                  | 0.4424           | 0.0             | 0.4424      |
+| 0.0467        | 5.7803 | 1000 | 0.0511          | 0.2238   | 0.4477        | 0.4477           | nan                  | 0.4477           | 0.0             | 0.4477      |
+
+
+### Framework versions
+
+- Transformers 4.43.0.dev0
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1