update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- preprocessed1024_config
+metrics:
+- accuracy
+- f1
+model-index:
+- name: vit-model
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: preprocessed1024_config
+      type: preprocessed1024_config
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value:
+        accuracy: 0.5615577889447236
+    - name: F1
+      type: f1
+      value:
+        f1: 0.5213901124963216
+---
+
+<!-- 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
+
+This model is a fine-tuned version of [](https://huggingface.co/) on the preprocessed1024_config dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9396
+- Accuracy: {'accuracy': 0.5615577889447236}
+- F1: {'f1': 0.5213901124963216}
+
+## 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: 5e-05
+- 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: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy                         | F1                         |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|:--------------------------:|
+| 1.221         | 1.0   | 796  | 0.9396          | {'accuracy': 0.5615577889447236} | {'f1': 0.5213901124963216} |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.12.0
+- Datasets 2.1.0
+- Tokenizers 0.12.1