Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/resnet-101
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: resnet-101-CivilEng11k_3Classes
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 1.0
+---
+
+<!-- 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. -->
+
+# resnet-101-CivilEng11k_3Classes
+
+This model is a fine-tuned version of [microsoft/resnet-101](https://huggingface.co/microsoft/resnet-101) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0002
+- Accuracy: 1.0
+
+## 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: 0.0002
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.0885        | 1.0   | 37   | 0.8955          | 0.4305   |
+| 0.6832        | 2.0   | 74   | 0.4990          | 0.8475   |
+| 0.2591        | 3.0   | 111  | 0.0587          | 1.0      |
+| 0.024         | 4.0   | 148  | 0.0026          | 1.0      |
+| 0.005         | 5.0   | 185  | 0.0007          | 1.0      |
+| 0.0121        | 6.0   | 222  | 0.0005          | 1.0      |
+| 0.0214        | 7.0   | 259  | 0.0003          | 1.0      |
+| 0.0035        | 8.0   | 296  | 0.0002          | 1.0      |
+| 0.0026        | 9.0   | 333  | 0.0002          | 1.0      |
+| 0.0054        | 10.0  | 370  | 0.0002          | 1.0      |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 1.12.1
+- Datasets 2.18.0
+- Tokenizers 0.15.1

model.safetensors

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