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--- |
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license: apache-2.0 |
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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: swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-eurosat-50 |
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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: Augmented |
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split: train |
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args: Augmented |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 1.0 |
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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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# swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-eurosat-50 |
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This model is a fine-tuned version of [microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0004 |
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- Accuracy: 1.0 |
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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: 3e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 0.05 |
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- num_epochs: 30 |
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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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| 1.5952 | 1.0 | 55 | 0.8490 | 0.6693 | |
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| 0.7582 | 2.0 | 110 | 0.4561 | 0.8386 | |
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| 0.4359 | 3.0 | 165 | 0.2408 | 0.9227 | |
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| 0.318 | 4.0 | 220 | 0.1294 | 0.9568 | |
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| 0.2414 | 5.0 | 275 | 0.0346 | 0.9909 | |
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| 0.1888 | 6.0 | 330 | 0.0419 | 0.9864 | |
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| 0.1717 | 7.0 | 385 | 0.0238 | 0.9943 | |
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| 0.1785 | 8.0 | 440 | 0.0230 | 0.9943 | |
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| 0.1654 | 9.0 | 495 | 0.0076 | 1.0 | |
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| 0.1322 | 10.0 | 550 | 0.0046 | 1.0 | |
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| 0.1123 | 11.0 | 605 | 0.0035 | 1.0 | |
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| 0.0953 | 12.0 | 660 | 0.0025 | 1.0 | |
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| 0.0864 | 13.0 | 715 | 0.0033 | 1.0 | |
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| 0.0984 | 14.0 | 770 | 0.0033 | 0.9989 | |
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| 0.0952 | 15.0 | 825 | 0.0015 | 1.0 | |
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| 0.0678 | 16.0 | 880 | 0.0022 | 1.0 | |
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| 0.0592 | 17.0 | 935 | 0.0013 | 1.0 | |
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| 0.0729 | 18.0 | 990 | 0.0037 | 0.9989 | |
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| 0.0672 | 19.0 | 1045 | 0.0041 | 0.9989 | |
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| 0.0615 | 20.0 | 1100 | 0.0010 | 1.0 | |
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| 0.058 | 21.0 | 1155 | 0.0009 | 1.0 | |
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| 0.0571 | 22.0 | 1210 | 0.0021 | 0.9989 | |
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| 0.0755 | 23.0 | 1265 | 0.0022 | 0.9989 | |
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| 0.0688 | 24.0 | 1320 | 0.0025 | 0.9989 | |
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| 0.0417 | 25.0 | 1375 | 0.0003 | 1.0 | |
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| 0.0589 | 26.0 | 1430 | 0.0007 | 1.0 | |
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| 0.0563 | 27.0 | 1485 | 0.0007 | 1.0 | |
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| 0.0603 | 28.0 | 1540 | 0.0010 | 0.9989 | |
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| 0.0469 | 29.0 | 1595 | 0.0005 | 1.0 | |
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| 0.0525 | 30.0 | 1650 | 0.0004 | 1.0 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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