Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/vit-large-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vit-large-patch16-224-dungeon-geo-morphs-0-4-29Nov24-001
+  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: 0.9946428571428572
+---
+
+<!-- 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-large-patch16-224-dungeon-geo-morphs-0-4-29Nov24-001
+
+This model is a fine-tuned version of [google/vit-large-patch16-224](https://huggingface.co/google/vit-large-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1522
+- Accuracy: 0.9946
+
+## 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: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Use 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_ratio: 0.1
+- num_epochs: 35
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.6512        | 4.0   | 10   | 1.3078          | 0.4643   |
+| 1.0709        | 8.0   | 20   | 0.7778          | 0.8429   |
+| 0.6487        | 12.0  | 30   | 0.4804          | 0.9089   |
+| 0.4013        | 16.0  | 40   | 0.3228          | 0.9554   |
+| 0.264         | 20.0  | 50   | 0.2140          | 0.9839   |
+| 0.1821        | 24.0  | 60   | 0.1688          | 0.9857   |
+| 0.1711        | 28.0  | 70   | 0.1522          | 0.9946   |
+
+
+### Framework versions
+
+- Transformers 4.46.2
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3