Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/resnet-18
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: resnet-18
+  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-18
+
+This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7117
+- 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| No log        | 0.9091 | 5    | 1.0318          | 0.4156   |
+| 1.0893        | 2.0    | 11   | 0.9520          | 0.6364   |
+| 1.0893        | 2.9091 | 16   | 0.9017          | 0.8442   |
+| 0.9912        | 4.0    | 22   | 0.8444          | 1.0      |
+| 0.9912        | 4.9091 | 27   | 0.8027          | 1.0      |
+| 0.9248        | 6.0    | 33   | 0.7631          | 1.0      |
+| 0.9248        | 6.9091 | 38   | 0.7369          | 1.0      |
+| 0.8716        | 8.0    | 44   | 0.7156          | 1.0      |
+| 0.8716        | 8.9091 | 49   | 0.7137          | 1.0      |
+| 0.8517        | 9.0909 | 50   | 0.7117          | 1.0      |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

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