End of training

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
+- precision
+- recall
+- f1
+model-index:
+- name: vit_itri_2class_downsample
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8977272727272727
+    - name: Precision
+      type: precision
+      value: 0.9210261342224775
+    - name: Recall
+      type: recall
+      value: 0.8977272727272727
+    - name: F1
+      type: f1
+      value: 0.9067029271654793
+---
+
+<!-- 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_itri_2class_downsample
+
+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: 0.0067
+- Accuracy: 0.8977
+- Precision: 0.9210
+- Recall: 0.8977
+- F1: 0.9067
+
+## 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: 0.0001
+- train_batch_size: 24
+- eval_batch_size: 4
+- seed: 42
+- 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
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.0067        | 1.0   | 197  | 0.0019          | 0.8628   | 0.9198    | 0.8628 | 0.8826 |
+| 0.0005        | 2.0   | 394  | 0.0013          | 0.9040   | 0.9025    | 0.9040 | 0.9032 |
+| 0.0005        | 3.0   | 591  | 0.0016          | 0.9191   | 0.9054    | 0.9191 | 0.8959 |
+| 0.0005        | 4.0   | 788  | 0.0021          | 0.8679   | 0.9180    | 0.8679 | 0.8858 |
+| 0.0001        | 5.0   | 985  | 0.0033          | 0.9102   | 0.9187    | 0.9102 | 0.9139 |
+| 0.0001        | 6.0   | 1182 | 0.0025          | 0.9151   | 0.9254    | 0.9151 | 0.9194 |
+| 0.0           | 7.0   | 1379 | 0.0038          | 0.8945   | 0.9218    | 0.8945 | 0.9048 |
+| 0.0           | 8.0   | 1576 | 0.0048          | 0.9090   | 0.9255    | 0.9090 | 0.9155 |
+| 0.0           | 9.0   | 1773 | 0.0066          | 0.8917   | 0.9198    | 0.8917 | 0.9024 |
+| 0.0           | 10.0  | 1970 | 0.0067          | 0.8977   | 0.9210    | 0.8977 | 0.9067 |
+
+
+### Framework versions
+
+- Transformers 4.53.0.dev0
+- Pytorch 2.7.1+cu126
+- Datasets 3.6.0
+- Tokenizers 0.21.1

model.safetensors

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