update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- cifar10
+metrics:
+- accuracy
+model-index:
+- name: AML_A2_Q4
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: cifar10
+      type: cifar10
+      config: plain_text
+      split: train[:]
+      args: plain_text
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9894
+---
+
+<!-- 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. -->
+
+# AML_A2_Q4
+
+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 cifar10 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0432
+- Accuracy: 0.9894
+
+## 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: 20
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.1642        | 1.0   | 2250 | 0.0572          | 0.9862   |
+| 0.1503        | 2.0   | 4500 | 0.0591          | 0.9854   |
+| 0.1818        | 3.0   | 6750 | 0.0432          | 0.9894   |
+
+
+### Framework versions
+
+- Transformers 4.28.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.12.0
+- Tokenizers 0.13.3