update model card README.md

README.md

@@ -0,0 +1,70 @@
+---
+license: other
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-v-mesh-0
+  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-v-mesh-0
+
+This model is a fine-tuned version of [nvidia/mit-b2](https://huggingface.co/nvidia/mit-b2) on the Onegafer/vehicle_segmentation dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0513
+- Mean Iou: 0.4015
+- Mean Accuracy: 0.8030
+- Overall Accuracy: 0.8030
+- Accuracy No: nan
+- Accuracy Yes: 0.8030
+- Iou No: 0.0
+- Iou Yes: 0.8030
+
+## 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: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy No | Accuracy Yes | Iou No | Iou Yes |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-----------:|:------------:|:------:|:-------:|
+| 0.2362        | 0.16  | 20   | 0.2073          | 0.2925   | 0.5849        | 0.5849           | nan         | 0.5849       | 0.0    | 0.5849  |
+| 0.1487        | 0.31  | 40   | 0.1029          | 0.3193   | 0.6386        | 0.6386           | nan         | 0.6386       | 0.0    | 0.6386  |
+| 0.0993        | 0.47  | 60   | 0.0861          | 0.4281   | 0.8562        | 0.8562           | nan         | 0.8562       | 0.0    | 0.8562  |
+| 0.1559        | 0.62  | 80   | 0.0603          | 0.3784   | 0.7568        | 0.7568           | nan         | 0.7568       | 0.0    | 0.7568  |
+| 0.0675        | 0.78  | 100  | 0.0536          | 0.3889   | 0.7777        | 0.7777           | nan         | 0.7777       | 0.0    | 0.7777  |
+| 0.0826        | 0.94  | 120  | 0.0513          | 0.4015   | 0.8030        | 0.8030           | nan         | 0.8030       | 0.0    | 0.8030  |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0+cu118
+- Datasets 2.11.0
+- Tokenizers 0.13.3