Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swin-tiny-patch4-window7-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: swin-tiny-patch4-window7-224-MM_Classification
+  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: 0.8872017353579176
+---
+
+<!-- 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-tiny-patch4-window7-224-MM_Classification
+
+This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2795
+- Accuracy: 0.8872
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 1.0635        | 0.9846 | 16   | 0.7524          | 0.6725   |
+| 0.4571        | 1.9692 | 32   | 0.3692          | 0.8742   |
+| 0.3819        | 2.9538 | 48   | 0.3500          | 0.8688   |
+| 0.3278        | 4.0    | 65   | 0.3158          | 0.8796   |
+| 0.2941        | 4.9846 | 81   | 0.2886          | 0.8883   |
+| 0.2912        | 5.9692 | 97   | 0.2895          | 0.8915   |
+| 0.2575        | 6.9538 | 113  | 0.2801          | 0.8839   |
+| 0.2604        | 8.0    | 130  | 0.2847          | 0.8861   |
+| 0.2519        | 8.9846 | 146  | 0.2804          | 0.8872   |
+| 0.2592        | 9.8462 | 160  | 0.2795          | 0.8872   |
+
+
+### Framework versions
+
+- Transformers 4.43.2
+- Pytorch 1.13.1+cu117
+- Datasets 2.20.0
+- Tokenizers 0.19.1

model.safetensors

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