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: food101-vit-base-patch16-224-in21k
+  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. -->
+
+# food101-vit-base-patch16-224-in21k
+
+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: 0.3894
+- Accuracy: 0.9072
+
+## 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: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 1337
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10.0
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.9431        | 1.0   | 9469  | 0.6777          | 0.8593   |
+| 0.617         | 2.0   | 18938 | 0.4546          | 0.8802   |
+| 0.9109        | 3.0   | 28407 | 0.4086          | 0.8899   |
+| 1.0346        | 4.0   | 37876 | 0.3911          | 0.8968   |
+| 0.2142        | 5.0   | 47345 | 0.4098          | 0.8913   |
+| 0.7247        | 6.0   | 56814 | 0.3904          | 0.9008   |
+| 0.3935        | 7.0   | 66283 | 0.3873          | 0.9035   |
+| 0.552         | 8.0   | 75752 | 0.3915          | 0.9053   |
+| 0.4012        | 9.0   | 85221 | 0.3955          | 0.9052   |
+| 0.2699        | 10.0  | 94690 | 0.3894          | 0.9072   |
+
+
+### Framework versions
+
+- Transformers 4.38.0
+- Pytorch 2.1.2+cu118
+- Datasets 2.19.1
+- Tokenizers 0.15.2

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