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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-humeda-2 |
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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-humeda-2 |
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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: 0.7928 |
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- Accuracy: 0.7115 |
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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: 40 |
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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 | 1.0 | 2 | 1.3469 | 0.5 | |
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| No log | 2.0 | 4 | 1.3200 | 0.4808 | |
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| No log | 3.0 | 6 | 1.3124 | 0.4808 | |
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| No log | 4.0 | 8 | 1.2178 | 0.5 | |
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| 1.1551 | 5.0 | 10 | 1.0957 | 0.5769 | |
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| 1.1551 | 6.0 | 12 | 1.0359 | 0.5769 | |
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| 1.1551 | 7.0 | 14 | 1.0103 | 0.5962 | |
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| 1.1551 | 8.0 | 16 | 0.9382 | 0.6538 | |
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| 1.1551 | 9.0 | 18 | 0.8748 | 0.6346 | |
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| 0.9827 | 10.0 | 20 | 0.8836 | 0.6154 | |
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| 0.9827 | 11.0 | 22 | 0.8574 | 0.6154 | |
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| 0.9827 | 12.0 | 24 | 0.8494 | 0.5962 | |
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| 0.9827 | 13.0 | 26 | 0.8226 | 0.6154 | |
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| 0.9827 | 14.0 | 28 | 0.8242 | 0.6346 | |
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| 0.8007 | 15.0 | 30 | 0.8304 | 0.6154 | |
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| 0.8007 | 16.0 | 32 | 0.8447 | 0.6538 | |
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| 0.8007 | 17.0 | 34 | 0.8228 | 0.6923 | |
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| 0.8007 | 18.0 | 36 | 0.7928 | 0.7115 | |
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| 0.8007 | 19.0 | 38 | 0.7822 | 0.6731 | |
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| 0.6882 | 20.0 | 40 | 0.7750 | 0.6538 | |
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| 0.6882 | 21.0 | 42 | 0.7726 | 0.6538 | |
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| 0.6882 | 22.0 | 44 | 0.7898 | 0.6731 | |
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| 0.6882 | 23.0 | 46 | 0.8021 | 0.6731 | |
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| 0.6882 | 24.0 | 48 | 0.7834 | 0.6923 | |
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| 0.6154 | 25.0 | 50 | 0.7634 | 0.6731 | |
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| 0.6154 | 26.0 | 52 | 0.7584 | 0.6923 | |
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| 0.6154 | 27.0 | 54 | 0.7773 | 0.6538 | |
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| 0.6154 | 28.0 | 56 | 0.7830 | 0.6538 | |
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| 0.6154 | 29.0 | 58 | 0.7719 | 0.6538 | |
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| 0.541 | 30.0 | 60 | 0.7603 | 0.6538 | |
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| 0.541 | 31.0 | 62 | 0.7497 | 0.6731 | |
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| 0.541 | 32.0 | 64 | 0.7381 | 0.7115 | |
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| 0.541 | 33.0 | 66 | 0.7275 | 0.6923 | |
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| 0.541 | 34.0 | 68 | 0.7277 | 0.6923 | |
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| 0.5163 | 35.0 | 70 | 0.7271 | 0.6923 | |
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| 0.5163 | 36.0 | 72 | 0.7274 | 0.6923 | |
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| 0.5163 | 37.0 | 74 | 0.7304 | 0.6923 | |
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| 0.5163 | 38.0 | 76 | 0.7329 | 0.6923 | |
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| 0.5163 | 39.0 | 78 | 0.7351 | 0.6923 | |
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| 0.5183 | 40.0 | 80 | 0.7356 | 0.6923 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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