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
+- f1
+model-index:
+- name: Fine-Tuned_Model3
+  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: 0.592
+    - name: F1
+      type: f1
+      value: 0.43854957441913966
+---
+
+<!-- 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. -->
+
+# Fine-Tuned_Model3
+
+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: 0.8979
+- Accuracy: 0.592
+- F1: 0.4385
+
+## 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: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| No log        | 5.0   | 20   | 2.0563          | 0.512    | 0.2812 |
+| No log        | 10.0  | 40   | 1.4346          | 0.576    | 0.3752 |
+| 2.1474        | 15.0  | 60   | 1.3222          | 0.576    | 0.3873 |
+| 2.1474        | 20.0  | 80   | 1.2946          | 0.576    | 0.3880 |
+| 1.2873        | 25.0  | 100  | 1.0957          | 0.6      | 0.4013 |
+| 1.2873        | 30.0  | 120  | 0.8979          | 0.592    | 0.4385 |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1