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: van-base-finetuned-eurosat-imgaug
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: image_folder
+      type: image_folder
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9885185185185185
+---
+
+<!-- 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. -->
+
+# van-base-finetuned-eurosat-imgaug
+
+This model is a fine-tuned version of [Visual-Attention-Network/van-base](https://huggingface.co/Visual-Attention-Network/van-base) on the image_folder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0379
+- Accuracy: 0.9885
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.0887        | 1.0   | 190  | 0.0589          | 0.98     |
+| 0.055         | 2.0   | 380  | 0.0390          | 0.9878   |
+| 0.0223        | 3.0   | 570  | 0.0379          | 0.9885   |
+
+
+### Framework versions
+
+- Transformers 4.18.0
+- Pytorch 1.10.0+cu111
+- Datasets 2.0.0
+- Tokenizers 0.11.6