Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swin-base-patch4-window7-224-in22k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: swin-base-patch4-window7-224-in22k-MM_Classification_base_V2
+  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: 0.8758002560819462
+---
+
+<!-- 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. -->
+
+# swin-base-patch4-window7-224-in22k-MM_Classification_base_V2
+
+This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2967
+- Accuracy: 0.8758
+
+## 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: 128
+- eval_batch_size: 128
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 512
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 7
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.0086        | 1.0   | 19   | 0.4613          | 0.8105   |
+| 0.4528        | 2.0   | 38   | 0.3454          | 0.8592   |
+| 0.3556        | 3.0   | 57   | 0.3289          | 0.8604   |
+| 0.3404        | 4.0   | 76   | 0.3197          | 0.8784   |
+| 0.3175        | 5.0   | 95   | 0.3018          | 0.8822   |
+| 0.3007        | 6.0   | 114  | 0.3007          | 0.8809   |
+| 0.2968        | 7.0   | 133  | 0.2967          | 0.8758   |
+
+
+### Framework versions
+
+- Transformers 4.43.3
+- Pytorch 1.13.1+cu117
+- Datasets 2.20.0
+- Tokenizers 0.19.1

model.safetensors

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