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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-U-40 |
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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-U-40 |
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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: 0.1175 |
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- Accuracy: 0.9817 |
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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 | 0.9 | 7 | 1.3839 | 0.3028 | |
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| 1.4343 | 1.94 | 15 | 1.3643 | 0.2844 | |
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| 1.3413 | 2.97 | 23 | 1.3310 | 0.3578 | |
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| 1.2473 | 4.0 | 31 | 1.1081 | 0.5138 | |
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| 1.2473 | 4.9 | 38 | 0.8292 | 0.7064 | |
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| 1.0532 | 5.94 | 46 | 0.7420 | 0.6239 | |
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| 0.917 | 6.97 | 54 | 0.6345 | 0.6972 | |
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| 0.7939 | 8.0 | 62 | 0.4898 | 0.8532 | |
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| 0.7939 | 8.9 | 69 | 0.5918 | 0.7523 | |
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| 0.7457 | 9.94 | 77 | 0.5271 | 0.7615 | |
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| 0.6834 | 10.97 | 85 | 0.3296 | 0.9450 | |
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| 0.5847 | 12.0 | 93 | 0.2883 | 0.9174 | |
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| 0.5199 | 12.9 | 100 | 0.2896 | 0.9266 | |
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| 0.5199 | 13.94 | 108 | 0.2859 | 0.8991 | |
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| 0.4657 | 14.97 | 116 | 0.2515 | 0.9083 | |
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| 0.4585 | 16.0 | 124 | 0.2261 | 0.9083 | |
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| 0.3892 | 16.9 | 131 | 0.2142 | 0.9266 | |
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| 0.3892 | 17.94 | 139 | 0.1788 | 0.9450 | |
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| 0.3939 | 18.97 | 147 | 0.1948 | 0.9266 | |
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| 0.3429 | 20.0 | 155 | 0.1685 | 0.9450 | |
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| 0.3493 | 20.9 | 162 | 0.1986 | 0.9083 | |
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| 0.3462 | 21.94 | 170 | 0.1540 | 0.9358 | |
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| 0.3462 | 22.97 | 178 | 0.1449 | 0.9450 | |
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| 0.3117 | 24.0 | 186 | 0.1379 | 0.9541 | |
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| 0.3109 | 24.9 | 193 | 0.1423 | 0.9450 | |
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| 0.2867 | 25.94 | 201 | 0.1451 | 0.9450 | |
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| 0.2867 | 26.97 | 209 | 0.1154 | 0.9725 | |
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| 0.293 | 28.0 | 217 | 0.1152 | 0.9541 | |
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| 0.2782 | 28.9 | 224 | 0.1261 | 0.9633 | |
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| 0.2744 | 29.94 | 232 | 0.1175 | 0.9817 | |
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| 0.2711 | 30.97 | 240 | 0.1292 | 0.9633 | |
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| 0.2711 | 32.0 | 248 | 0.1101 | 0.9817 | |
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| 0.2652 | 32.9 | 255 | 0.1202 | 0.9633 | |
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| 0.2218 | 33.94 | 263 | 0.1119 | 0.9817 | |
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| 0.2899 | 34.97 | 271 | 0.1071 | 0.9817 | |
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| 0.2899 | 36.0 | 279 | 0.1077 | 0.9817 | |
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| 0.2143 | 36.13 | 280 | 0.1077 | 0.9817 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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