Model save

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vit-base-25ep
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8486111111111111
+---
+
+<!-- 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-base-25ep
+
+This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5506
+- Accuracy: 0.8486
+
+## 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: 0.0003
+- train_batch_size: 64
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 25
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.6167        | 1.0   | 275  | 0.5712          | 0.8354   |
+| 0.3183        | 2.0   | 550  | 0.5564          | 0.8406   |
+| 0.1729        | 3.0   | 825  | 0.5955          | 0.8433   |
+| 0.139         | 4.0   | 1100 | 0.6453          | 0.8406   |
+| 0.0775        | 5.0   | 1375 | 0.6044          | 0.8517   |
+| 0.0784        | 6.0   | 1650 | 0.7265          | 0.8414   |
+| 0.0502        | 7.0   | 1925 | 0.6977          | 0.8533   |
+| 0.0525        | 8.0   | 2200 | 0.7100          | 0.8549   |
+| 0.0311        | 9.0   | 2475 | 0.7423          | 0.8525   |
+| 0.026         | 10.0  | 2750 | 0.7901          | 0.8461   |
+| 0.0183        | 11.0  | 3025 | 0.7261          | 0.8592   |
+| 0.0218        | 12.0  | 3300 | 0.8014          | 0.8485   |
+| 0.0135        | 13.0  | 3575 | 0.7391          | 0.8584   |
+| 0.0066        | 14.0  | 3850 | 0.6938          | 0.8740   |
+| 0.0047        | 15.0  | 4125 | 0.6765          | 0.8815   |
+| 0.0052        | 16.0  | 4400 | 0.6611          | 0.8839   |
+| 0.0033        | 17.0  | 4675 | 0.6794          | 0.8803   |
+| 0.0037        | 18.0  | 4950 | 0.6724          | 0.8811   |
+| 0.0026        | 19.0  | 5225 | 0.6759          | 0.8875   |
+| 0.0031        | 20.0  | 5500 | 0.6699          | 0.8855   |
+| 0.0028        | 21.0  | 5775 | 0.6720          | 0.8847   |
+| 0.0029        | 22.0  | 6050 | 0.6746          | 0.8843   |
+| 0.0016        | 23.0  | 6325 | 0.6731          | 0.8859   |
+| 0.0016        | 24.0  | 6600 | 0.6759          | 0.8859   |
+| 0.0019        | 25.0  | 6875 | 0.6767          | 0.8847   |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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runs/May21_17-05-00_ccd549edd53e/events.out.tfevents.1716330092.ccd549edd53e.24.1

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