Model save

README.md

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+---
+license: other
+base_model: nvidia/mit-b5
+tags:
+- generated_from_trainer
+model-index:
+- name: ecc_segformerv3
+  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. -->
+
+# ecc_segformerv3
+
+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: 0.1344
+- Mean Iou: 0.0005
+- Mean Accuracy: 0.0010
+- Overall Accuracy: 0.0010
+- Accuracy Background: nan
+- Accuracy Crack: 0.0010
+- Iou Background: 0.0
+- Iou Crack: 0.0010
+
+## 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: 0.0006
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 5000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Crack | Iou Background | Iou Crack |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:--------------:|:--------------:|:---------:|
+| 0.1306        | 1.0   | 1001 | 0.1114          | 0.0      | 0.0           | 0.0              | nan                 | 0.0            | 0.0            | 0.0       |
+| 0.107         | 2.0   | 2002 | 0.1238          | 0.0000   | 0.0000        | 0.0000           | nan                 | 0.0000         | 0.0            | 0.0000    |
+| 0.1285        | 3.0   | 3003 | 0.1631          | 0.0024   | 0.0049        | 0.0049           | nan                 | 0.0049         | 0.0            | 0.0048    |
+| 0.0887        | 4.0   | 4004 | 0.1083          | 0.0002   | 0.0003        | 0.0003           | nan                 | 0.0003         | 0.0            | 0.0003    |
+| 0.0828        | 5.0   | 5000 | 0.1344          | 0.0005   | 0.0010        | 0.0010           | nan                 | 0.0010         | 0.0            | 0.0010    |
+
+
+### Framework versions
+
+- Transformers 4.32.0.dev0
+- Pytorch 2.0.1+cpu
+- Datasets 2.14.4
+- Tokenizers 0.13.3