Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: WinKawaks/vit-tiny-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vit-tiny-patch16-224-finetuned-papsmear
+  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: 0.9338235294117647
+---
+
+<!-- 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. -->
+
+# vit-tiny-patch16-224-finetuned-papsmear
+
+This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1882
+- Accuracy: 0.9338
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|
+| 1.4005        | 0.9935  | 38   | 1.2214          | 0.5294   |
+| 0.8877        | 1.9869  | 76   | 1.0727          | 0.6691   |
+| 0.603         | 2.9804  | 114  | 0.6807          | 0.7574   |
+| 0.465         | 4.0     | 153  | 0.6485          | 0.7574   |
+| 0.432         | 4.9935  | 191  | 0.5024          | 0.8015   |
+| 0.2957        | 5.9869  | 229  | 0.4485          | 0.8162   |
+| 0.2203        | 6.9804  | 267  | 0.3850          | 0.8529   |
+| 0.236         | 8.0     | 306  | 0.3628          | 0.8456   |
+| 0.1857        | 8.9935  | 344  | 0.2930          | 0.8824   |
+| 0.1907        | 9.9869  | 382  | 0.2121          | 0.9338   |
+| 0.1546        | 10.9804 | 420  | 0.2242          | 0.9265   |
+| 0.1375        | 12.0    | 459  | 0.1918          | 0.9191   |
+| 0.1237        | 12.9935 | 497  | 0.1809          | 0.9338   |
+| 0.1637        | 13.9869 | 535  | 0.1774          | 0.9338   |
+| 0.0803        | 14.9020 | 570  | 0.1882          | 0.9338   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu121
+- Datasets 3.0.0
+- Tokenizers 0.19.1

model.safetensors

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