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-brand
+  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: 0.8411297440423654
+---
+
+<!-- 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-brand
+
+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: 0.5083
+- Accuracy: 0.8411
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.2977        | 0.99  | 106  | 1.0930          | 0.6580   |
+| 0.9557        | 2.0   | 213  | 0.8573          | 0.7273   |
+| 0.7349        | 3.0   | 320  | 0.7455          | 0.7617   |
+| 0.5729        | 4.0   | 427  | 0.6196          | 0.8063   |
+| 0.4818        | 4.99  | 533  | 0.5769          | 0.8147   |
+| 0.395         | 6.0   | 640  | 0.5788          | 0.8182   |
+| 0.3222        | 7.0   | 747  | 0.5594          | 0.8310   |
+| 0.3729        | 8.0   | 854  | 0.5453          | 0.8252   |
+| 0.265         | 8.99  | 960  | 0.5289          | 0.8389   |
+| 0.2409        | 10.0  | 1067 | 0.5249          | 0.8345   |
+| 0.1557        | 11.0  | 1174 | 0.5125          | 0.8433   |
+| 0.1811        | 12.0  | 1281 | 0.5123          | 0.8486   |
+| 0.1616        | 12.99 | 1387 | 0.5142          | 0.8491   |
+| 0.1481        | 14.0  | 1494 | 0.5107          | 0.8420   |
+| 0.1526        | 14.89 | 1590 | 0.5083          | 0.8411   |
+
+
+### Framework versions
+
+- Transformers 4.35.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

model.safetensors

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