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-finetuned-brain-tumor-classification
+  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: 0.8905191873589164
+---
+
+<!-- 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-finetuned-brain-tumor-classification
+
+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: 0.4348
+- Accuracy: 0.8905
+
+## 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: 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: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 3.1659        | 0.9897 | 48   | 2.4060          | 0.4086   |
+| 1.8381        | 2.0    | 97   | 1.2904          | 0.6772   |
+| 1.0781        | 2.9897 | 145  | 0.9211          | 0.7573   |
+| 0.8049        | 4.0    | 194  | 0.7274          | 0.8036   |
+| 0.6091        | 4.9897 | 242  | 0.6427          | 0.8330   |
+| 0.4985        | 6.0    | 291  | 0.5519          | 0.8510   |
+| 0.4077        | 6.9897 | 339  | 0.4921          | 0.8792   |
+| 0.3583        | 8.0    | 388  | 0.4756          | 0.8826   |
+| 0.3292        | 8.9897 | 436  | 0.4472          | 0.8883   |
+| 0.338         | 9.8969 | 480  | 0.4348          | 0.8905   |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

runs/Jul18_18-18-25_5defc8b690ca/events.out.tfevents.1721326743.5defc8b690ca.332.0

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