Model save

README.md

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+---
+license: apache-2.0
+base_model: DouglasBraga/swin-tiny-patch4-window7-224-finetuned-eurosat-leukemia-3000
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: swin-tiny-patch4-window7-224-finetuned-eurosat-leukemia-3000-finetuned-leukemia-1000
+  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. -->
+
+# swin-tiny-patch4-window7-224-finetuned-eurosat-leukemia-3000-finetuned-leukemia-1000
+
+This model is a fine-tuned version of [DouglasBraga/swin-tiny-patch4-window7-224-finetuned-eurosat-leukemia-3000](https://huggingface.co/DouglasBraga/swin-tiny-patch4-window7-224-finetuned-eurosat-leukemia-3000) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0026
+- 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.5471        | 0.9825 | 14   | 0.1240          | 0.955    |
+| 0.1792        | 1.9649 | 28   | 0.0493          | 0.985    |
+| 0.0936        | 2.9474 | 42   | 0.1210          | 0.965    |
+| 0.0907        | 4.0    | 57   | 0.0056          | 1.0      |
+| 0.0441        | 4.9825 | 71   | 0.0165          | 0.995    |
+| 0.0341        | 5.9649 | 85   | 0.0059          | 0.995    |
+| 0.0406        | 6.9474 | 99   | 0.0018          | 1.0      |
+| 0.013         | 8.0    | 114  | 0.0200          | 0.995    |
+| 0.0342        | 8.9825 | 128  | 0.0030          | 1.0      |
+| 0.0246        | 9.8246 | 140  | 0.0026          | 1.0      |
+
+
+### Framework versions
+
+- Transformers 4.40.0.dev0
+- Pytorch 2.2.2+cpu
+- Datasets 2.19.0
+- Tokenizers 0.15.2

model.safetensors

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