Model save

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: snacks_classification
+  results: []
+---
+
+<!-- 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. -->
+
+# snacks_classification
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4458
+- Accuracy: 0.8942
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 13
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 303  | 0.7200          | 0.8649   |
+| 1.0168        | 2.0   | 606  | 0.5468          | 0.8723   |
+| 1.0168        | 3.0   | 909  | 0.4612          | 0.8848   |
+| 0.3765        | 4.0   | 1212 | 0.5239          | 0.8660   |
+| 0.2585        | 5.0   | 1515 | 0.4193          | 0.8890   |
+| 0.2585        | 6.0   | 1818 | 0.4571          | 0.8775   |
+| 0.2038        | 7.0   | 2121 | 0.4538          | 0.8838   |
+| 0.2038        | 8.0   | 2424 | 0.4508          | 0.8880   |
+| 0.1827        | 9.0   | 2727 | 0.4748          | 0.8880   |
+| 0.1568        | 10.0  | 3030 | 0.4928          | 0.8764   |
+| 0.1568        | 11.0  | 3333 | 0.3684          | 0.9099   |
+| 0.1305        | 12.0  | 3636 | 0.4205          | 0.8984   |
+| 0.1305        | 13.0  | 3939 | 0.4537          | 0.8963   |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.1
+- Tokenizers 0.15.2

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