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README.md
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---
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license: apache-2.0
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base_model: google/vit-base-patch16-224-in21k
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: ViTuned_buildings
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results: []
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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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# ViTuned_buildings
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0432
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- Accuracy: 0.9931
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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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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- num_epochs: 4
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.1985 | 0.33 | 100 | 1.1271 | 0.9726 |
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| 0.4085 | 0.67 | 200 | 0.3959 | 0.9743 |
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| 0.186 | 1.0 | 300 | 0.1963 | 0.9846 |
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| 0.1066 | 1.34 | 400 | 0.2404 | 0.9417 |
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| 0.1117 | 1.67 | 500 | 0.1423 | 0.9726 |
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| 0.0923 | 2.01 | 600 | 0.1076 | 0.9794 |
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| 0.0315 | 2.34 | 700 | 0.0656 | 0.9846 |
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| 0.0263 | 2.68 | 800 | 0.0645 | 0.9880 |
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| 0.0542 | 3.01 | 900 | 0.0458 | 0.9949 |
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| 0.0203 | 3.34 | 1000 | 0.0444 | 0.9931 |
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| 0.0189 | 3.68 | 1100 | 0.0432 | 0.9931 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.1.2
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- Datasets 2.1.0
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- Tokenizers 0.15.2
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