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---
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
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