update model card README.md

README.md

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+---
+license: other
+base_model: nvidia/mit-b5
+tags:
+- generated_from_trainer
+model-index:
+- name: segcrack9k_conglomerate_train_test
+  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. -->
+
+# segcrack9k_conglomerate_train_test
+
+This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0298
+- Mean Iou: 0.3639
+- Mean Accuracy: 0.7278
+- Overall Accuracy: 0.7278
+- Accuracy Background: nan
+- Accuracy Crack: 0.7278
+- Iou Background: 0.0
+- Iou Crack: 0.7278
+
+## 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 Background | Accuracy Crack | Iou Background | Iou Crack |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:--------------:|:--------------:|:---------:|
+| 0.0374        | 0.18  | 1000 | 0.0410          | 0.2472   | 0.4944        | 0.4944           | nan                 | 0.4944         | 0.0            | 0.4944    |
+| 0.0337        | 0.36  | 2000 | 0.0341          | 0.3749   | 0.7497        | 0.7497           | nan                 | 0.7497         | 0.0            | 0.7497    |
+| 0.0209        | 0.55  | 3000 | 0.0318          | 0.3335   | 0.6670        | 0.6670           | nan                 | 0.6670         | 0.0            | 0.6670    |
+| 0.0099        | 0.73  | 4000 | 0.0315          | 0.3371   | 0.6743        | 0.6743           | nan                 | 0.6743         | 0.0            | 0.6743    |
+| 0.026         | 0.91  | 5000 | 0.0298          | 0.3639   | 0.7278        | 0.7278           | nan                 | 0.7278         | 0.0            | 0.7278    |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.0
+- Tokenizers 0.13.3