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-5e-4
+  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: 0.8682539682539683
+---
+
+<!-- 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-5e-4
+
+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: 0.6221
+- Accuracy: 0.8683
+
+## 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: 0.0005
+- train_batch_size: 64
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.7552        | 1.0   | 275  | 0.7489          | 0.7849   |
+| 0.4161        | 2.0   | 550  | 0.6816          | 0.8127   |
+| 0.2389        | 3.0   | 825  | 0.6486          | 0.8326   |
+| 0.1523        | 4.0   | 1100 | 0.6459          | 0.8414   |
+| 0.0917        | 5.0   | 1375 | 0.7039          | 0.8382   |
+| 0.0492        | 6.0   | 1650 | 0.7023          | 0.8425   |
+| 0.0175        | 7.0   | 1925 | 0.6089          | 0.8664   |
+| 0.009         | 8.0   | 2200 | 0.5864          | 0.8775   |
+| 0.0026        | 9.0   | 2475 | 0.5646          | 0.8783   |
+| 0.0037        | 10.0  | 2750 | 0.5681          | 0.8803   |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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runs/May21_15-09-26_fc712b13befb/events.out.tfevents.1716312876.fc712b13befb.24.1

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