update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- mnist
+metrics:
+- accuracy
+model-index:
+- name: vit-base-mnist
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: mnist
+      type: mnist
+      config: mnist
+      split: train
+      args: mnist
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9947777777777778
+---
+
+<!-- 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-mnist
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the mnist dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0236
+- Accuracy: 0.9948
+
+## 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: 5.0
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.379         | 1.0   | 6375  | 0.0506          | 0.9896   |
+| 0.3384        | 2.0   | 12750 | 0.0362          | 0.9906   |
+| 0.3605        | 3.0   | 19125 | 0.0313          | 0.9923   |
+| 0.3252        | 4.0   | 25500 | 0.0262          | 0.9938   |
+| 0.2885        | 5.0   | 31875 | 0.0236          | 0.9948   |
+
+
+### Framework versions
+
+- Transformers 4.22.0.dev0
+- Pytorch 1.11.0a0+17540c5
+- Datasets 2.4.0
+- Tokenizers 0.12.1