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
+- precision
+- recall
+- f1
+model-index:
+- name: vit-base-oxford-brain-tumor_x-ray
+  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: 0.7692307692307693
+    - name: Precision
+      type: precision
+      value: 0.7692307692307693
+    - name: Recall
+      type: recall
+      value: 0.7692307692307693
+    - name: F1
+      type: f1
+      value: 0.7692307692307693
+---
+
+<!-- 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-oxford-brain-tumor_x-ray
+
+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: 0.5912
+- Accuracy: 0.7692
+- Precision: 0.7692
+- Recall: 0.7692
+- F1: 0.7692
+
+## 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: 0.0003
+- train_batch_size: 20
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.6752        | 1.0   | 11   | 0.4894          | 0.76     | 0.7148    | 0.76   | 0.7114 |
+| 0.5673        | 2.0   | 22   | 0.4630          | 0.72     | 0.57      | 0.72   | 0.6363 |
+| 0.6173        | 3.0   | 33   | 0.4269          | 0.92     | 0.92      | 0.92   | 0.92   |
+| 0.5562        | 4.0   | 44   | 0.5047          | 0.84     | 0.8653    | 0.84   | 0.8470 |
+| 0.5285        | 5.0   | 55   | 0.4036          | 0.92     | 0.92      | 0.92   | 0.92   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

runs/Jun13_11-15-55_60cbcd28d8fc/events.out.tfevents.1718278296.60cbcd28d8fc.42279.1

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