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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: swin-tiny-patch4-window7-224-finetuned-agrivision |
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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: 0.9202733485193622 |
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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-agrivision |
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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: 0.3605 |
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- Accuracy: 0.9203 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 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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| 0.5913 | 1.0 | 31 | 0.7046 | 0.7175 | |
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| 0.1409 | 2.0 | 62 | 0.8423 | 0.6788 | |
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| 0.0825 | 3.0 | 93 | 0.6224 | 0.7654 | |
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| 0.0509 | 4.0 | 124 | 0.4379 | 0.8360 | |
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| 0.0439 | 5.0 | 155 | 0.1706 | 0.9317 | |
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| 0.0107 | 6.0 | 186 | 0.1914 | 0.9362 | |
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| 0.0134 | 7.0 | 217 | 0.2491 | 0.9089 | |
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| 0.0338 | 8.0 | 248 | 0.2119 | 0.9362 | |
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| 0.0306 | 9.0 | 279 | 0.4502 | 0.8610 | |
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| 0.0054 | 10.0 | 310 | 0.4990 | 0.8747 | |
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| 0.0033 | 11.0 | 341 | 0.2746 | 0.9112 | |
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| 0.0021 | 12.0 | 372 | 0.2501 | 0.9317 | |
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| 0.0068 | 13.0 | 403 | 0.1883 | 0.9522 | |
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| 0.0038 | 14.0 | 434 | 0.3672 | 0.9134 | |
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| 0.0006 | 15.0 | 465 | 0.2275 | 0.9408 | |
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| 0.0011 | 16.0 | 496 | 0.3349 | 0.9134 | |
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| 0.0017 | 17.0 | 527 | 0.3329 | 0.9157 | |
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| 0.0007 | 18.0 | 558 | 0.2508 | 0.9317 | |
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| 0.0023 | 19.0 | 589 | 0.2338 | 0.9385 | |
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| 0.0003 | 20.0 | 620 | 0.3193 | 0.9226 | |
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| 0.002 | 21.0 | 651 | 0.4604 | 0.9043 | |
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| 0.0023 | 22.0 | 682 | 0.3338 | 0.9203 | |
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| 0.005 | 23.0 | 713 | 0.2925 | 0.9271 | |
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| 0.0001 | 24.0 | 744 | 0.2022 | 0.9522 | |
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| 0.0002 | 25.0 | 775 | 0.2699 | 0.9339 | |
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| 0.0007 | 26.0 | 806 | 0.2603 | 0.9385 | |
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| 0.0005 | 27.0 | 837 | 0.4120 | 0.9134 | |
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| 0.0003 | 28.0 | 868 | 0.3550 | 0.9203 | |
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| 0.0008 | 29.0 | 899 | 0.3657 | 0.9203 | |
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| 0.0 | 30.0 | 930 | 0.3605 | 0.9203 | |
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### Framework versions |
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- Transformers 4.21.1 |
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- Pytorch 1.12.1 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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