update model card README.md

README.md

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+---
+tags:
+- image-classification
+- generated_from_trainer
+datasets:
+- cifar10
+metrics:
+- accuracy
+model-index:
+- name: vit_cifar10_classification_tmp
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: cifar10
+      type: cifar10
+      config: plain_text
+      split: test
+      args: plain_text
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9781
+---
+
+<!-- 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_cifar10_classification_tmp
+
+This model is a fine-tuned version of [againeureka/vit_cifar10_classification_tmp](https://huggingface.co/againeureka/vit_cifar10_classification_tmp) on the cifar10 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0945
+- Accuracy: 0.9781
+
+## 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: 128
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2199        | 0.26  | 100  | 0.1853          | 0.9678   |
+| 0.0999        | 0.51  | 200  | 0.1270          | 0.9713   |
+| 0.0944        | 0.77  | 300  | 0.0945          | 0.9781   |
+
+
+### Framework versions
+
+- Transformers 4.29.1
+- Pytorch 2.0.0+cu118
+- Datasets 2.12.0
+- Tokenizers 0.13.2