Model save

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vit-base-patch16-224
+  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: 0.6984126984126984
+---
+
+<!-- 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-patch16-224
+
+This model was trained from scratch on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6466
+- Accuracy: 0.6984
+
+## 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-06
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.6893        | 1.0   | 35   | 0.7319          | 0.4127   |
+| 0.702         | 2.0   | 70   | 0.6863          | 0.5238   |
+| 0.6644        | 3.0   | 105  | 0.6796          | 0.5873   |
+| 0.645         | 4.0   | 140  | 0.6722          | 0.5714   |
+| 0.6455        | 5.0   | 175  | 0.6545          | 0.6508   |
+| 0.6456        | 6.0   | 210  | 0.6536          | 0.6508   |
+| 0.6745        | 7.0   | 245  | 0.6463          | 0.6984   |
+| 0.6369        | 8.0   | 280  | 0.6525          | 0.6667   |
+| 0.6012        | 9.0   | 315  | 0.6486          | 0.6984   |
+| 0.6219        | 10.0  | 350  | 0.6466          | 0.6984   |
+
+
+### Framework versions
+
+- Transformers 4.43.3
+- Pytorch 2.4.0+cu118
+- Datasets 2.20.0
+- Tokenizers 0.19.1

model.safetensors

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