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# vit-base-patch16-224-in21k-finetuned-eurosat

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 imagefolder dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2695
- eval_accuracy: 0.9022
- eval_runtime: 195.5267
- eval_samples_per_second: 21.486
- eval_steps_per_second: 0.675
- epoch: 51.76
- step: 10196

## 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: 200

### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.1+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1

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