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-pure-ViT
+  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: 0.8714733542319749
+---
+
+<!-- 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-pure-ViT
+
+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: 0.3270
+- Accuracy: 0.8715
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.4676        | 1.0   | 202  | 0.4042          | 0.8095   |
+| 0.4605        | 2.0   | 404  | 0.3675          | 0.8377   |
+| 0.4012        | 3.0   | 606  | 0.3486          | 0.8506   |
+| 0.3727        | 4.0   | 808  | 0.3413          | 0.8481   |
+| 0.3482        | 5.0   | 1010 | 0.3339          | 0.8614   |
+| 0.354         | 6.0   | 1212 | 0.3436          | 0.8561   |
+| 0.3212        | 7.0   | 1414 | 0.3415          | 0.8534   |
+| 0.3263        | 8.0   | 1616 | 0.3281          | 0.8642   |
+| 0.285         | 9.0   | 1818 | 0.3263          | 0.8673   |
+| 0.2779        | 10.0  | 2020 | 0.3270          | 0.8715   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

runs/Mar18_05-17-36_9a8860256273/events.out.tfevents.1710739057.9a8860256273.3136.1

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