Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/resnet-152
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: Resnet152-5e-5
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7614314115308151
+---
+
+<!-- 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. -->
+
+# Resnet152-5e-5
+
+This model is a fine-tuned version of [microsoft/resnet-152](https://huggingface.co/microsoft/resnet-152) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8255
+- Accuracy: 0.7614
+
+## 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: 5e-05
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 3.2352        | 1.0   | 275  | 2.9196          | 0.1984   |
+| 2.5896        | 2.0   | 550  | 1.9631          | 0.4736   |
+| 1.8864        | 3.0   | 825  | 1.3420          | 0.6231   |
+| 1.5969        | 4.0   | 1100 | 1.1232          | 0.6918   |
+| 1.465         | 5.0   | 1375 | 0.9717          | 0.7213   |
+| 1.371         | 6.0   | 1650 | 0.9014          | 0.7483   |
+| 1.2795        | 7.0   | 1925 | 0.8566          | 0.7491   |
+| 1.2448        | 8.0   | 2200 | 0.8272          | 0.7594   |
+| 1.2234        | 9.0   | 2475 | 0.8145          | 0.7630   |
+| 1.2143        | 10.0  | 2750 | 0.8255          | 0.7614   |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

model.safetensors

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