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-patch16-224-RX1-24
+  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: 0.803921568627451
+---
+
+<!-- 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-RX1-24
+
+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: 0.6337
+- Accuracy: 0.8039
+
+## 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: 5.5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.05
+- num_epochs: 24
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.93  | 7    | 1.3485          | 0.4706   |
+| 1.3674        | 2.0   | 15   | 1.2284          | 0.5490   |
+| 1.2414        | 2.93  | 22   | 1.1307          | 0.6471   |
+| 1.1146        | 4.0   | 30   | 1.0230          | 0.6471   |
+| 1.1146        | 4.93  | 37   | 0.9251          | 0.6863   |
+| 0.9522        | 6.0   | 45   | 0.9122          | 0.6471   |
+| 0.8247        | 6.93  | 52   | 0.9374          | 0.6275   |
+| 0.6825        | 8.0   | 60   | 0.8320          | 0.6863   |
+| 0.6825        | 8.93  | 67   | 0.8286          | 0.6667   |
+| 0.6191        | 10.0  | 75   | 0.8418          | 0.6667   |
+| 0.5312        | 10.93 | 82   | 0.7836          | 0.8235   |
+| 0.454         | 12.0  | 90   | 0.7356          | 0.8039   |
+| 0.454         | 12.93 | 97   | 0.6117          | 0.8235   |
+| 0.3752        | 14.0  | 105  | 0.6014          | 0.8235   |
+| 0.3269        | 14.93 | 112  | 0.6102          | 0.8039   |
+| 0.2733        | 16.0  | 120  | 0.6404          | 0.8039   |
+| 0.2733        | 16.93 | 127  | 0.5687          | 0.8431   |
+| 0.2711        | 18.0  | 135  | 0.6120          | 0.8235   |
+| 0.2519        | 18.93 | 142  | 0.6250          | 0.8431   |
+| 0.2484        | 20.0  | 150  | 0.6086          | 0.7843   |
+| 0.2484        | 20.93 | 157  | 0.6229          | 0.8235   |
+| 0.2258        | 22.0  | 165  | 0.6390          | 0.7843   |
+| 0.2258        | 22.4  | 168  | 0.6337          | 0.8039   |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.2+cu118
+- Datasets 2.16.1
+- Tokenizers 0.15.0

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