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

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Accuracy: 0.0224

## 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: 4e-05
- train_batch_size: 96
- eval_batch_size: 96
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 384
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss                            | Epoch | Step | Validation Loss | Accuracy |
|:----------------------------------------:|:-----:|:----:|:---------------:|:--------:|
| 18403482038360886413349920928956416.0000 | 1.0   | 258  | inf             | 0.0224   |
| 18462639726606223815285376672595968.0000 | 2.0   | 517  | inf             | 0.0224   |
| 18309578839444917002657010957680640.0000 | 3.0   | 775  | inf             | 0.0224   |
| 18496480055520128970480019132383232.0000 | 4.0   | 1034 | inf             | 0.0224   |
| 18428848915293890075301730177777664.0000 | 4.99  | 1290 | inf             | 0.0224   |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224", "model-index": [{"name": "vit-base-patch16-224-finetuned-eurosat", "results": []}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer base_model:google/vit-base-patch16-224 license:apache-2.0 autotrain_compatible endpoints_compatible region:us