Model save

README.md

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+---
+library_name: transformers
+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-finetuned-leukemia-08-2024.v1.2
+  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: 0.74475
+---
+
+<!-- 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-finetuned-leukemia-08-2024.v1.2
+
+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: 1.1793
+- Accuracy: 0.7448
+
+## 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
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.471         | 0.9984 | 312  | 0.5907          | 0.6715   |
+| 0.3376        | 2.0    | 625  | 0.8904          | 0.702    |
+| 0.2266        | 2.9984 | 937  | 1.8065          | 0.556    |
+| 0.2529        | 4.0    | 1250 | 0.8170          | 0.713    |
+| 0.1925        | 4.9984 | 1562 | 1.0643          | 0.6907   |
+| 0.177         | 6.0    | 1875 | 1.2558          | 0.6843   |
+| 0.1563        | 6.9984 | 2187 | 0.9205          | 0.7445   |
+| 0.1417        | 8.0    | 2500 | 0.6624          | 0.8063   |
+| 0.1284        | 8.9984 | 2812 | 1.1648          | 0.739    |
+| 0.0805        | 9.984  | 3120 | 1.1793          | 0.7448   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu118
+- Datasets 2.21.0
+- Tokenizers 0.19.1

model.safetensors

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