Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/vit-large-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vit-large-patch16-224-in21k-dungeon-geo-morphs-0-4-30Nov24-004
+  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: 0.9625
+---
+
+<!-- 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-in21k-dungeon-geo-morphs-0-4-30Nov24-004
+
+This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](https://huggingface.co/google/vit-large-patch16-224-in21k) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1275
+- Accuracy: 0.9625
+
+## 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: 2e-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: 40
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|
+| 1.3834        | 3.9091  | 10   | 1.1055          | 0.7929   |
+| 0.5606        | 7.9091  | 20   | 0.5141          | 0.9286   |
+| 0.13          | 11.9091 | 30   | 0.2629          | 0.9518   |
+| 0.0283        | 15.9091 | 40   | 0.1654          | 0.9464   |
+| 0.0082        | 19.9091 | 50   | 0.1352          | 0.9554   |
+| 0.0043        | 23.9091 | 60   | 0.1337          | 0.9589   |
+| 0.0033        | 27.9091 | 70   | 0.1257          | 0.9607   |
+| 0.0029        | 31.9091 | 80   | 0.1275          | 0.9625   |
+
+
+### Framework versions
+
+- Transformers 4.46.2
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

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