---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: beit-base-patch16-224-pt22k-finetuned-eurosat
  results: []
---

<!-- 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. -->

# beit-base-patch16-224-pt22k-finetuned-eurosat

This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9338
- Accuracy: 0.6667

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 3    | 1.3657          | 0.3095   |
| No log        | 2.0   | 6    | 1.1966          | 0.4286   |
| No log        | 3.0   | 9    | 1.1076          | 0.4524   |
| 1.2696        | 4.0   | 12   | 1.0717          | 0.5714   |
| 1.2696        | 5.0   | 15   | 0.9948          | 0.5238   |
| 1.2696        | 6.0   | 18   | 1.0701          | 0.5      |
| 1.0945        | 7.0   | 21   | 0.9920          | 0.5      |
| 1.0945        | 8.0   | 24   | 0.9338          | 0.6667   |
| 1.0945        | 9.0   | 27   | 0.9605          | 0.5714   |
| 0.9538        | 10.0  | 30   | 0.9285          | 0.6190   |
| 0.9538        | 11.0  | 33   | 0.9113          | 0.5714   |
| 0.9538        | 12.0  | 36   | 0.8414          | 0.6190   |
| 0.9538        | 13.0  | 39   | 0.9422          | 0.5476   |
| 0.8646        | 14.0  | 42   | 0.8165          | 0.6429   |
| 0.8646        | 15.0  | 45   | 0.9582          | 0.5238   |
| 0.8646        | 16.0  | 48   | 0.8548          | 0.6190   |
| 0.8082        | 17.0  | 51   | 0.8568          | 0.6190   |
| 0.8082        | 18.0  | 54   | 0.8792          | 0.5476   |
| 0.8082        | 19.0  | 57   | 0.8819          | 0.5476   |
| 0.7731        | 20.0  | 60   | 0.8454          | 0.5714   |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.13.3