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--- |
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license: apache-2.0 |
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base_model: microsoft/swinv2-tiny-patch4-window8-256 |
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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: swinv2-tiny-patch4-window8-256-dmae-va-U5-42B |
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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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# swinv2-tiny-patch4-window8-256-dmae-va-U5-42B |
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This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8386 |
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- Accuracy: 0.65 |
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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: 4e-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: 42 |
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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 | 0.9 | 7 | 6.1748 | 0.1167 | |
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| 5.327 | 1.94 | 15 | 6.0660 | 0.1167 | |
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| 5.327 | 2.97 | 23 | 5.4902 | 0.1167 | |
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| 5.0963 | 4.0 | 31 | 4.2768 | 0.1167 | |
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| 3.9193 | 4.9 | 38 | 3.0013 | 0.1167 | |
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| 3.9193 | 5.94 | 46 | 1.9289 | 0.1167 | |
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| 2.2222 | 6.97 | 54 | 1.3857 | 0.1167 | |
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| 1.4465 | 8.0 | 62 | 1.3423 | 0.4333 | |
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| 1.4465 | 8.9 | 69 | 1.2786 | 0.45 | |
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| 1.3709 | 9.94 | 77 | 1.2654 | 0.4667 | |
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| 1.3511 | 10.97 | 85 | 1.2605 | 0.4667 | |
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| 1.3511 | 12.0 | 93 | 1.2184 | 0.4667 | |
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| 1.2749 | 12.9 | 100 | 1.2894 | 0.5 | |
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| 1.222 | 13.94 | 108 | 1.2072 | 0.5167 | |
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| 1.222 | 14.97 | 116 | 1.1749 | 0.5167 | |
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| 1.1668 | 16.0 | 124 | 1.1988 | 0.5167 | |
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| 1.1668 | 16.9 | 131 | 1.2306 | 0.5167 | |
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| 1.101 | 17.94 | 139 | 1.1432 | 0.5333 | |
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| 1.029 | 18.97 | 147 | 1.0208 | 0.55 | |
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| 1.029 | 20.0 | 155 | 0.9577 | 0.6167 | |
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| 0.9403 | 20.9 | 162 | 0.9479 | 0.5 | |
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| 0.8887 | 21.94 | 170 | 0.8910 | 0.5833 | |
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| 0.8887 | 22.97 | 178 | 0.9442 | 0.5333 | |
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| 0.8506 | 24.0 | 186 | 0.8923 | 0.6 | |
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| 0.8064 | 24.9 | 193 | 0.8973 | 0.6 | |
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| 0.8064 | 25.94 | 201 | 0.9079 | 0.55 | |
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| 0.7434 | 26.97 | 209 | 0.8386 | 0.65 | |
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| 0.7404 | 28.0 | 217 | 0.8645 | 0.6167 | |
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| 0.7404 | 28.9 | 224 | 0.8599 | 0.5667 | |
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| 0.7215 | 29.94 | 232 | 0.8420 | 0.65 | |
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| 0.6743 | 30.97 | 240 | 0.8553 | 0.5667 | |
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| 0.6743 | 32.0 | 248 | 0.8355 | 0.6167 | |
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| 0.6767 | 32.9 | 255 | 0.8694 | 0.5833 | |
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| 0.6767 | 33.94 | 263 | 0.8559 | 0.65 | |
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| 0.6606 | 34.97 | 271 | 0.8351 | 0.6167 | |
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| 0.6488 | 36.0 | 279 | 0.8287 | 0.6333 | |
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| 0.6488 | 36.9 | 286 | 0.8377 | 0.6167 | |
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| 0.6544 | 37.94 | 294 | 0.8406 | 0.6 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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