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-RXL1-24
+  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: 0.7647058823529411
+---
+
+<!-- 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-RXL1-24
+
+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: 0.7772
+- Accuracy: 0.7647
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.3745        | 0.95  | 13   | 1.3056          | 0.4706   |
+| 1.2896        | 1.96  | 27   | 1.1039          | 0.6471   |
+| 0.9896        | 2.98  | 41   | 0.9413          | 0.6471   |
+| 0.8472        | 4.0   | 55   | 0.9059          | 0.6275   |
+| 0.7375        | 4.95  | 68   | 0.6520          | 0.8039   |
+| 0.458         | 5.96  | 82   | 0.6754          | 0.8039   |
+| 0.3807        | 6.98  | 96   | 0.6158          | 0.8431   |
+| 0.3003        | 8.0   | 110  | 0.5666          | 0.8039   |
+| 0.2337        | 8.95  | 123  | 0.5409          | 0.8039   |
+| 0.2252        | 9.96  | 137  | 0.7382          | 0.7647   |
+| 0.1644        | 10.98 | 151  | 0.6363          | 0.8039   |
+| 0.1608        | 12.0  | 165  | 0.6941          | 0.8039   |
+| 0.1354        | 12.95 | 178  | 0.6985          | 0.7843   |
+| 0.1298        | 13.96 | 192  | 0.6610          | 0.8039   |
+| 0.1333        | 14.98 | 206  | 0.6751          | 0.8039   |
+| 0.1209        | 16.0  | 220  | 0.7723          | 0.7843   |
+| 0.1057        | 16.95 | 233  | 0.8038          | 0.7255   |
+| 0.0972        | 17.96 | 247  | 0.8375          | 0.7647   |
+| 0.0789        | 18.98 | 261  | 0.6971          | 0.8235   |
+| 0.0833        | 20.0  | 275  | 0.7507          | 0.7843   |
+| 0.0813        | 20.95 | 288  | 0.7085          | 0.7843   |
+| 0.0803        | 21.96 | 302  | 0.7566          | 0.7647   |
+| 0.0693        | 22.69 | 312  | 0.7772          | 0.7647   |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.2+cu118
+- Datasets 2.16.1
+- Tokenizers 0.15.0

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