Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swinv2-base-patch4-window8-256
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: swinv2-base-patch4-window8-256
+  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: 0.813953488372093
+---
+
+<!-- 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. -->
+
+# swinv2-base-patch4-window8-256
+
+This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window8-256](https://huggingface.co/microsoft/swinv2-base-patch4-window8-256) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4871
+- Accuracy: 0.8140
+
+## 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-06
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- 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        | 0.96  | 6    | 0.6027          | 0.7907   |
+| 0.6492        | 1.92  | 12   | 0.5212          | 0.8140   |
+| 0.6492        | 2.88  | 18   | 0.4939          | 0.8140   |
+| 0.5773        | 4.0   | 25   | 0.4829          | 0.8140   |
+| 0.6313        | 4.96  | 31   | 0.4833          | 0.8140   |
+| 0.6313        | 5.92  | 37   | 0.4873          | 0.8140   |
+| 0.5665        | 6.88  | 43   | 0.4876          | 0.8140   |
+| 0.5615        | 8.0   | 50   | 0.4861          | 0.8140   |
+| 0.5615        | 8.96  | 56   | 0.4873          | 0.8140   |
+| 0.5712        | 9.6   | 60   | 0.4871          | 0.8140   |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.3.1+cu118
+- Datasets 2.20.0
+- Tokenizers 0.19.1

model.safetensors

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