Model save

README.md

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+---
+license: apache-2.0
+base_model: facebook/convnext-tiny-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: convnext-tiny-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: 0.7794117647058824
+---
+
+<!-- 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. -->
+
+# convnext-tiny-224-finetuned-papsmear
+
+This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6010
+- Accuracy: 0.7794
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- 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 |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|
+| 1.8151        | 0.9870  | 19   | 1.6491          | 0.3456   |
+| 1.6104        | 1.9740  | 38   | 1.4322          | 0.4265   |
+| 1.4002        | 2.9610  | 57   | 1.2286          | 0.5882   |
+| 1.203         | 4.0     | 77   | 1.0559          | 0.6544   |
+| 1.047         | 4.9870  | 96   | 0.9357          | 0.6765   |
+| 0.9083        | 5.9740  | 115  | 0.8477          | 0.7279   |
+| 0.8756        | 6.9610  | 134  | 0.7762          | 0.75     |
+| 0.7853        | 8.0     | 154  | 0.7258          | 0.7647   |
+| 0.7198        | 8.9870  | 173  | 0.7023          | 0.7574   |
+| 0.7151        | 9.9740  | 192  | 0.6756          | 0.7574   |
+| 0.7049        | 10.9610 | 211  | 0.6493          | 0.7574   |
+| 0.6387        | 12.0    | 231  | 0.6256          | 0.7721   |
+| 0.6387        | 12.9870 | 250  | 0.6295          | 0.7721   |
+| 0.6233        | 13.9740 | 269  | 0.6033          | 0.7794   |
+| 0.632         | 14.8052 | 285  | 0.6010          | 0.7794   |
+
+
+### Framework versions
+
+- Transformers 4.44.0
+- Pytorch 2.4.0
+- Datasets 2.21.0
+- Tokenizers 0.19.1

model.safetensors

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