update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- image_folder
+metrics:
+- accuracy
+model-index:
+- name: vitmae-large-funnydataset
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: image_folder
+      type: image_folder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.49783549783549785
+---
+
+<!-- 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. -->
+
+# vitmae-large-funnydataset
+
+This model is a fine-tuned version of [facebook/vit-mae-large](https://huggingface.co/facebook/vit-mae-large) on the image_folder dataset.
+It achieves the following results on the evaluation set:
+- Loss: nan
+- Accuracy: 0.4978
+
+## 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: 1e-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: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.0           | 0.55  | 100  | nan             | 0.4978   |
+| 0.0           | 1.1   | 200  | nan             | 0.4978   |
+| 0.0           | 1.66  | 300  | nan             | 0.4978   |
+| 0.0           | 2.21  | 400  | nan             | 0.4978   |
+| 0.0           | 2.76  | 500  | nan             | 0.4978   |
+| 0.0           | 3.31  | 600  | nan             | 0.4978   |
+| 0.0           | 3.87  | 700  | nan             | 0.4978   |
+
+
+### Framework versions
+
+- Transformers 4.30.1
+- Pytorch 2.0.0
+- Datasets 2.1.0
+- Tokenizers 0.13.3