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update model card README.md

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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - image_folder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: vit-base-patch16-224-finetuned-eurosat
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: image_folder
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+ type: image_folder
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9071691176470589
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # vit-base-patch16-224-finetuned-eurosat
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the image_folder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3209
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+ - Accuracy: 0.9072
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.5417 | 0.99 | 76 | 0.5556 | 0.8263 |
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+ | 0.4853 | 1.99 | 152 | 0.5319 | 0.8199 |
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+ | 0.4926 | 2.99 | 228 | 0.5133 | 0.8539 |
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+ | 0.4131 | 3.99 | 304 | 0.4481 | 0.8603 |
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+ | 0.4081 | 4.99 | 380 | 0.4280 | 0.8824 |
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+ | 0.3287 | 5.99 | 456 | 0.4330 | 0.8667 |
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+ | 0.3381 | 6.99 | 532 | 0.3549 | 0.8888 |
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+ | 0.3182 | 7.99 | 608 | 0.3382 | 0.8961 |
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+ | 0.3046 | 8.99 | 684 | 0.3790 | 0.8925 |
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+ | 0.3093 | 9.99 | 760 | 0.3209 | 0.9072 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.18.0
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+ - Pytorch 1.11.0+cu113
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+ - Datasets 2.1.0
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+ - Tokenizers 0.12.1