Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: facebook/dinov2-small
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: dinov2-small-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: 0.8602941176470589
+---
+
+<!-- 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. -->
+
+# dinov2-small-finetuned-papsmear
+
+This model is a fine-tuned version of [facebook/dinov2-small](https://huggingface.co/facebook/dinov2-small) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3843
+- Accuracy: 0.8603
+
+## 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 |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|
+| 0.846         | 0.9935  | 38   | 1.0217          | 0.5956   |
+| 1.0241        | 1.9869  | 76   | 0.8413          | 0.6544   |
+| 0.9178        | 2.9804  | 114  | 0.7204          | 0.7426   |
+| 0.693         | 4.0     | 153  | 0.5731          | 0.75     |
+| 0.7157        | 4.9935  | 191  | 0.5501          | 0.8162   |
+| 0.5006        | 5.9869  | 229  | 0.6096          | 0.7794   |
+| 0.4576        | 6.9804  | 267  | 0.5535          | 0.7941   |
+| 0.467         | 8.0     | 306  | 0.5041          | 0.8162   |
+| 0.4378        | 8.9935  | 344  | 0.5771          | 0.8015   |
+| 0.2876        | 9.9869  | 382  | 0.4234          | 0.8456   |
+| 0.2308        | 10.9804 | 420  | 0.4946          | 0.8382   |
+| 0.2312        | 12.0    | 459  | 0.5098          | 0.8309   |
+| 0.1625        | 12.9935 | 497  | 0.3813          | 0.8603   |
+| 0.1775        | 13.9869 | 535  | 0.3695          | 0.8529   |
+| 0.1358        | 14.9020 | 570  | 0.3843          | 0.8603   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1

model.safetensors

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