End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/vit-large-patch32-384
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: image_classification
+  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: 0.3
+---
+
+<!-- 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. -->
+
+# image_classification
+
+This model is a fine-tuned version of [google/vit-large-patch32-384](https://huggingface.co/google/vit-large-patch32-384) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.8452
+- Accuracy: 0.3
+
+## 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: 3e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.1828        | 1.0   | 20   | 2.1899          | 0.1125   |
+| 2.1419        | 2.0   | 40   | 2.1018          | 0.1625   |
+| 2.078         | 3.0   | 60   | 2.1286          | 0.1625   |
+| 2.0943        | 4.0   | 80   | 2.1462          | 0.15     |
+| 2.0486        | 5.0   | 100  | 2.0665          | 0.2      |
+| 1.9442        | 6.0   | 120  | 1.9868          | 0.2562   |
+| 1.9307        | 7.0   | 140  | 1.9403          | 0.2375   |
+| 1.8743        | 8.0   | 160  | 1.8866          | 0.275    |
+| 1.7348        | 9.0   | 180  | 1.7927          | 0.3312   |
+| 1.6455        | 10.0  | 200  | 1.7579          | 0.3187   |
+
+
+### Framework versions
+
+- Transformers 4.48.3
+- Pytorch 2.5.1+cu124
+- Datasets 3.3.2
+- Tokenizers 0.21.0

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