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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-PE |
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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: 0.797979797979798 |
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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-PE |
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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: 0.4489 |
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- Accuracy: 0.7980 |
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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: 0.0025 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 512 |
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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: 50 |
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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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| 0.6872 | 1.0 | 11 | 0.6535 | 0.6061 | |
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| 0.7287 | 2.0 | 22 | 0.6601 | 0.6397 | |
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| 0.7212 | 3.0 | 33 | 0.6740 | 0.5657 | |
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| 0.6947 | 4.0 | 44 | 0.6531 | 0.6532 | |
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| 0.6783 | 5.0 | 55 | 0.6739 | 0.5724 | |
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| 0.6816 | 6.0 | 66 | 0.6274 | 0.6599 | |
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| 0.6428 | 7.0 | 77 | 0.6671 | 0.6330 | |
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| 0.6928 | 8.0 | 88 | 0.6380 | 0.6498 | |
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| 0.6767 | 9.0 | 99 | 0.6875 | 0.6061 | |
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| 0.6918 | 10.0 | 110 | 0.6859 | 0.5690 | |
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| 0.6845 | 11.0 | 121 | 0.6810 | 0.5657 | |
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| 0.6826 | 12.0 | 132 | 0.6919 | 0.5185 | |
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| 0.6877 | 13.0 | 143 | 0.6693 | 0.6061 | |
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| 0.6709 | 14.0 | 154 | 0.6660 | 0.5690 | |
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| 0.6707 | 15.0 | 165 | 0.6764 | 0.5690 | |
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| 0.6703 | 16.0 | 176 | 0.6467 | 0.6296 | |
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| 0.6629 | 17.0 | 187 | 0.6471 | 0.6431 | |
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| 0.6557 | 18.0 | 198 | 0.6597 | 0.6229 | |
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| 0.659 | 19.0 | 209 | 0.6451 | 0.6027 | |
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| 0.65 | 20.0 | 220 | 0.6638 | 0.6094 | |
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| 0.6453 | 21.0 | 231 | 0.6544 | 0.6162 | |
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| 0.6426 | 22.0 | 242 | 0.6565 | 0.5825 | |
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| 0.6339 | 23.0 | 253 | 0.6743 | 0.6296 | |
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| 0.6236 | 24.0 | 264 | 0.6669 | 0.5960 | |
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| 0.6427 | 25.0 | 275 | 0.6379 | 0.6532 | |
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| 0.6439 | 26.0 | 286 | 0.6361 | 0.6263 | |
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| 0.6212 | 27.0 | 297 | 0.6540 | 0.6465 | |
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| 0.6186 | 28.0 | 308 | 0.5925 | 0.6700 | |
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| 0.6162 | 29.0 | 319 | 0.6224 | 0.6734 | |
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| 0.6237 | 30.0 | 330 | 0.6018 | 0.6667 | |
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| 0.6061 | 31.0 | 341 | 0.5735 | 0.6801 | |
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| 0.6138 | 32.0 | 352 | 0.6425 | 0.6566 | |
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| 0.595 | 33.0 | 363 | 0.5827 | 0.6768 | |
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| 0.5869 | 34.0 | 374 | 0.5956 | 0.7172 | |
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| 0.577 | 35.0 | 385 | 0.5458 | 0.7003 | |
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| 0.5766 | 36.0 | 396 | 0.5603 | 0.6869 | |
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| 0.5726 | 37.0 | 407 | 0.5339 | 0.7340 | |
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| 0.5702 | 38.0 | 418 | 0.5577 | 0.7138 | |
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| 0.5762 | 39.0 | 429 | 0.5262 | 0.7374 | |
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| 0.5543 | 40.0 | 440 | 0.5091 | 0.7441 | |
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| 0.5339 | 41.0 | 451 | 0.5185 | 0.7542 | |
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| 0.5428 | 42.0 | 462 | 0.5023 | 0.7542 | |
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| 0.5349 | 43.0 | 473 | 0.5439 | 0.7306 | |
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| 0.5319 | 44.0 | 484 | 0.4745 | 0.7811 | |
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| 0.5294 | 45.0 | 495 | 0.5432 | 0.7172 | |
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| 0.5314 | 46.0 | 506 | 0.4511 | 0.7912 | |
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| 0.5073 | 47.0 | 517 | 0.4379 | 0.8047 | |
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| 0.5028 | 48.0 | 528 | 0.4487 | 0.7980 | |
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| 0.4985 | 49.0 | 539 | 0.4550 | 0.7946 | |
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| 0.4826 | 50.0 | 550 | 0.4489 | 0.7980 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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