Model save

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch32-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- snacks
+metrics:
+- accuracy
+model-index:
+- name: vit-model-rob-vilchis
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: snacks
+      type: snacks
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8607329842931937
+---
+
+<!-- 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-model-rob-vilchis
+
+This model is a fine-tuned version of [google/vit-base-patch32-224-in21k](https://huggingface.co/google/vit-base-patch32-224-in21k) on the snacks dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5765
+- Accuracy: 0.8607
+
+## 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: 0.0002
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.2646        | 0.83  | 500  | 0.9471          | 0.7361   |
+| 0.4485        | 1.65  | 1000 | 0.6931          | 0.8084   |
+| 0.179         | 2.48  | 1500 | 0.7448          | 0.8157   |
+| 0.052         | 3.31  | 2000 | 0.5765          | 0.8607   |
+
+
+### Framework versions
+
+- Transformers 4.33.1
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3