Model save

README.md

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+---
+license: other
+base_model: nvidia/mit-b0
+tags:
+- generated_from_trainer
+model-index:
+- name: segformer-finetuned-rwymarkings-2-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-rwymarkings-2-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: 2.2162
+- Mean Iou: 0.0387
+- Mean Accuracy: 0.1129
+- Overall Accuracy: 0.1050
+- Accuracy  Backgound : nan
+- Accuracy Tdz: 0.0493
+- Accuracy Aim: 0.2144
+- Accuracy Desig: 0.0922
+- Accuracy Rwythr: 0.1765
+- Accuracy Thrbar: 0.0140
+- Accuracy Disp: 0.2710
+- Accuracy Chevron: 0.0023
+- Accuracy Arrow: 0.0834
+- Iou  Backgound : 0.0
+- Iou Tdz: 0.0399
+- Iou Aim: 0.1158
+- Iou Desig: 0.0443
+- Iou Rwythr: 0.0980
+- Iou Thrbar: 0.0131
+- Iou Disp: 0.0266
+- Iou Chevron: 0.0020
+- Iou Arrow: 0.0085
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 1337
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: polynomial
+- training_steps: 2
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy  Backgound  | Accuracy Tdz | Accuracy Aim | Accuracy Desig | Accuracy Rwythr | Accuracy Thrbar | Accuracy Disp | Accuracy Chevron | Accuracy Arrow | Iou  Backgound  | Iou Tdz | Iou Aim | Iou Desig | Iou Rwythr | Iou Thrbar | Iou Disp | Iou Chevron | Iou Arrow |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------------:|:------------:|:------------:|:--------------:|:---------------:|:---------------:|:-------------:|:----------------:|:--------------:|:---------------:|:-------:|:-------:|:---------:|:----------:|:----------:|:--------:|:-----------:|:---------:|
+| 2.2475        | 0.0455 | 2    | 2.2162          | 0.0387   | 0.1129        | 0.1050           | nan                  | 0.0493       | 0.2144       | 0.0922         | 0.1765          | 0.0140          | 0.2710        | 0.0023           | 0.0834         | 0.0             | 0.0399  | 0.1158  | 0.0443    | 0.0980     | 0.0131     | 0.0266   | 0.0020      | 0.0085    |
+
+
+### Framework versions
+
+- Transformers 4.43.0.dev0
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1