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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: microsoft/swinv2-base-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-base-patch4-window8-256-dmae-humeda-DAV16 |
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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-base-patch4-window8-256-dmae-humeda-DAV16 |
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This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window8-256](https://huggingface.co/microsoft/swinv2-base-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: 1.0641 |
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- Accuracy: 0.75 |
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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 | 0.8696 | 5 | 1.5391 | 0.4038 | |
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| No log | 1.8696 | 10 | 1.4350 | 0.4231 | |
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| 6.5563 | 2.8696 | 15 | 1.3179 | 0.5385 | |
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| 6.5563 | 3.8696 | 20 | 1.2358 | 0.5385 | |
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| 4.5658 | 4.8696 | 25 | 0.9991 | 0.5769 | |
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| 4.5658 | 5.8696 | 30 | 0.9567 | 0.5385 | |
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| 4.5658 | 6.8696 | 35 | 0.8482 | 0.6154 | |
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| 2.7201 | 7.8696 | 40 | 1.1108 | 0.4615 | |
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| 2.7201 | 8.8696 | 45 | 0.7993 | 0.6923 | |
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| 1.9091 | 9.8696 | 50 | 0.8539 | 0.6154 | |
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| 1.9091 | 10.8696 | 55 | 0.8361 | 0.6731 | |
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| 1.6858 | 11.8696 | 60 | 0.8574 | 0.6731 | |
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| 1.6858 | 12.8696 | 65 | 0.9489 | 0.6346 | |
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| 1.6858 | 13.8696 | 70 | 0.8122 | 0.7115 | |
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| 1.2131 | 14.8696 | 75 | 0.8131 | 0.6538 | |
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| 1.2131 | 15.8696 | 80 | 0.8591 | 0.6731 | |
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| 0.8967 | 16.8696 | 85 | 0.9155 | 0.6538 | |
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| 0.8967 | 17.8696 | 90 | 0.9712 | 0.7115 | |
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| 0.8967 | 18.8696 | 95 | 0.9574 | 0.6731 | |
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| 0.8657 | 19.8696 | 100 | 1.0001 | 0.7115 | |
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| 0.8657 | 20.8696 | 105 | 1.1041 | 0.5962 | |
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| 0.6795 | 21.8696 | 110 | 1.0165 | 0.6923 | |
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| 0.6795 | 22.8696 | 115 | 1.0816 | 0.6538 | |
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| 0.5608 | 23.8696 | 120 | 1.1195 | 0.7308 | |
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| 0.5608 | 24.8696 | 125 | 1.0680 | 0.6923 | |
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| 0.5608 | 25.8696 | 130 | 1.1495 | 0.6923 | |
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| 0.6841 | 26.8696 | 135 | 1.0789 | 0.7115 | |
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| 0.6841 | 27.8696 | 140 | 1.0814 | 0.7115 | |
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| 0.4526 | 28.8696 | 145 | 1.0830 | 0.6923 | |
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| 0.4526 | 29.8696 | 150 | 1.0641 | 0.75 | |
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| 0.4526 | 30.8696 | 155 | 1.1337 | 0.6731 | |
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| 0.4067 | 31.8696 | 160 | 1.0867 | 0.6923 | |
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| 0.4067 | 32.8696 | 165 | 1.1103 | 0.6731 | |
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| 0.4003 | 33.8696 | 170 | 1.0909 | 0.6923 | |
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| 0.4003 | 34.8696 | 175 | 1.0950 | 0.6731 | |
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| 0.4415 | 35.8696 | 180 | 1.0712 | 0.7115 | |
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| 0.4415 | 36.8696 | 185 | 1.0569 | 0.7115 | |
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| 0.4415 | 37.8696 | 190 | 1.0618 | 0.6923 | |
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| 0.3715 | 38.8696 | 195 | 1.0770 | 0.6923 | |
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| 0.3715 | 39.8696 | 200 | 1.0976 | 0.6923 | |
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| 0.4178 | 40.8696 | 205 | 1.1072 | 0.6923 | |
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| 0.4178 | 41.8696 | 210 | 1.1047 | 0.6923 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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