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--- |
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license: apache-2.0 |
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base_model: microsoft/swin-tiny-patch4-window7-224 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: swin-tiny-patch4-window7-224-finetuned-eurosat |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.808641975308642 |
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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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# swin-tiny-patch4-window7-224-finetuned-eurosat |
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This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5712 |
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- Accuracy: 0.8086 |
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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: 5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 20 |
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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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| No log | 0.87 | 5 | 1.3767 | 0.5370 | |
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| 1.289 | 1.91 | 11 | 1.3503 | 0.5494 | |
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| 1.289 | 2.96 | 17 | 1.3712 | 0.5556 | |
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| 1.0376 | 4.0 | 23 | 1.3064 | 0.5556 | |
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| 1.0376 | 4.87 | 28 | 1.1062 | 0.5802 | |
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| 0.8346 | 5.91 | 34 | 0.9249 | 0.6481 | |
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| 0.7096 | 6.96 | 40 | 0.8947 | 0.6235 | |
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| 0.7096 | 8.0 | 46 | 0.8626 | 0.6543 | |
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| 0.6356 | 8.87 | 51 | 0.6820 | 0.7222 | |
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| 0.6356 | 9.91 | 57 | 0.7249 | 0.7346 | |
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| 0.5956 | 10.96 | 63 | 0.6818 | 0.7407 | |
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| 0.5956 | 12.0 | 69 | 0.6111 | 0.7840 | |
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| 0.5534 | 12.87 | 74 | 0.6026 | 0.7778 | |
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| 0.519 | 13.91 | 80 | 0.6070 | 0.7901 | |
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| 0.519 | 14.96 | 86 | 0.5758 | 0.7963 | |
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| 0.5117 | 16.0 | 92 | 0.5791 | 0.7840 | |
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| 0.5117 | 16.87 | 97 | 0.5711 | 0.8025 | |
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| 0.4913 | 17.39 | 100 | 0.5712 | 0.8086 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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