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: Augmented-MIT-b5
+  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. -->
+
+# Augmented-MIT-b5
+
+This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0371
+- Mean Iou: 0.3355
+- Mean Accuracy: 0.6711
+- Overall Accuracy: 0.6711
+- Accuracy Background: nan
+- Accuracy Crack: 0.6711
+- Iou Background: 0.0
+- Iou Crack: 0.6711
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:--------------:|:--------------:|:---------:|
+| 0.0365        | 0.14  | 1000 | 0.0446          | 0.3813   | 0.7627        | 0.7627           | nan                 | 0.7627         | 0.0            | 0.7627    |
+| 0.0114        | 0.27  | 2000 | 0.0411          | 0.3691   | 0.7381        | 0.7381           | nan                 | 0.7381         | 0.0            | 0.7381    |
+| 0.0148        | 0.41  | 3000 | 0.0400          | 0.3224   | 0.6448        | 0.6448           | nan                 | 0.6448         | 0.0            | 0.6448    |
+| 0.0134        | 0.54  | 4000 | 0.0413          | 0.2819   | 0.5638        | 0.5638           | nan                 | 0.5638         | 0.0            | 0.5638    |
+| 0.013         | 0.68  | 5000 | 0.0392          | 0.3618   | 0.7235        | 0.7235           | nan                 | 0.7235         | 0.0            | 0.7235    |
+| 0.0532        | 0.81  | 6000 | 0.0373          | 0.3355   | 0.6710        | 0.6710           | nan                 | 0.6710         | 0.0            | 0.6710    |
+| 0.0508        | 0.95  | 7000 | 0.0371          | 0.3355   | 0.6711        | 0.6711           | nan                 | 0.6711         | 0.0            | 0.6711    |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3