Model save

README.md

@@ -0,0 +1,101 @@
+---
+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-RU9-24
+  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: 0.8235294117647058
+---
+
+<!-- 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-RU9-24
+
+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: 0.5375
+- Accuracy: 0.8235
+
+## 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        | 1.0   | 8    | 1.3401          | 0.5098   |
+| 1.3685        | 2.0   | 16   | 1.2193          | 0.5686   |
+| 1.2413        | 3.0   | 24   | 1.1150          | 0.5882   |
+| 1.1126        | 4.0   | 32   | 0.9957          | 0.7059   |
+| 0.9285        | 5.0   | 40   | 0.8976          | 0.6863   |
+| 0.9285        | 6.0   | 48   | 0.8580          | 0.6863   |
+| 0.7793        | 7.0   | 56   | 0.8426          | 0.7647   |
+| 0.6291        | 8.0   | 64   | 0.7899          | 0.6863   |
+| 0.5401        | 9.0   | 72   | 0.7169          | 0.7255   |
+| 0.4358        | 10.0  | 80   | 0.7505          | 0.7255   |
+| 0.4358        | 11.0  | 88   | 0.8077          | 0.7059   |
+| 0.3901        | 12.0  | 96   | 0.6803          | 0.7647   |
+| 0.3033        | 13.0  | 104  | 0.6483          | 0.7647   |
+| 0.267         | 14.0  | 112  | 0.6451          | 0.7451   |
+| 0.2212        | 15.0  | 120  | 0.6119          | 0.7647   |
+| 0.2212        | 16.0  | 128  | 0.6150          | 0.8039   |
+| 0.2206        | 17.0  | 136  | 0.6270          | 0.7843   |
+| 0.2285        | 18.0  | 144  | 0.6181          | 0.7647   |
+| 0.1741        | 19.0  | 152  | 0.5081          | 0.8431   |
+| 0.1708        | 20.0  | 160  | 0.5502          | 0.8235   |
+| 0.1708        | 21.0  | 168  | 0.5689          | 0.8039   |
+| 0.16          | 22.0  | 176  | 0.5137          | 0.8235   |
+| 0.1567        | 23.0  | 184  | 0.5207          | 0.8431   |
+| 0.1616        | 24.0  | 192  | 0.5375          | 0.8235   |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.2+cu118
+- Datasets 2.16.1
+- Tokenizers 0.15.0

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