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README.md
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---
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library_name: transformers
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license: other
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base_model: facebook/mask2former-swin-tiny-coco-instance
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tags:
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- generated_from_trainer
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model-index:
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- name: finetune-instance-segmentation-ade20k-mini-mask2former_backbone_frozen_1
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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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# finetune-instance-segmentation-ade20k-mini-mask2former_backbone_frozen_1
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This model is a fine-tuned version of [facebook/mask2former-swin-tiny-coco-instance](https://huggingface.co/facebook/mask2former-swin-tiny-coco-instance) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 22.5821
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- Map: 0.181
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- Map 50: 0.35
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- Map 75: 0.164
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- Map Small: 0.0954
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- Map Medium: 0.3758
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- Map Large: 0.9135
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- Mar 1: 0.0856
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- Mar 10: 0.2359
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- Mar 100: 0.2819
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- Mar Small: 0.2158
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- Mar Medium: 0.4688
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- Mar Large: 0.9371
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- Map Car: 0.3473
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- Mar 100 Car: 0.4911
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- Map Person: 0.0147
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- Mar 100 Person: 0.0727
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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: 1e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 16
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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: constant
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- num_epochs: 10.0
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Map | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1 | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Car | Mar 100 Car | Map Person | Mar 100 Person |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:-------:|:-----------:|:----------:|:--------------:|
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| 36.0195 | 1.0 | 315 | 27.1721 | 0.1432 | 0.279 | 0.1349 | 0.0688 | 0.3117 | 0.8516 | 0.0714 | 0.1887 | 0.2291 | 0.1605 | 0.4115 | 0.9133 | 0.2849 | 0.4372 | 0.0014 | 0.0209 |
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| 28.6156 | 2.0 | 630 | 25.2879 | 0.1597 | 0.2996 | 0.1521 | 0.0779 | 0.337 | 0.8789 | 0.078 | 0.2055 | 0.2497 | 0.1825 | 0.4386 | 0.9173 | 0.3147 | 0.4628 | 0.0046 | 0.0367 |
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| 26.5961 | 3.0 | 945 | 24.4641 | 0.1679 | 0.3171 | 0.1572 | 0.0817 | 0.3481 | 0.8921 | 0.0809 | 0.2137 | 0.259 | 0.193 | 0.4441 | 0.9229 | 0.326 | 0.473 | 0.0098 | 0.045 |
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| 25.435 | 4.0 | 1260 | 24.1017 | 0.1701 | 0.3217 | 0.1577 | 0.0815 | 0.3562 | 0.9002 | 0.0816 | 0.2169 | 0.2601 | 0.1929 | 0.4479 | 0.9272 | 0.329 | 0.469 | 0.0112 | 0.0512 |
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| 24.7221 | 5.0 | 1575 | 23.5551 | 0.1738 | 0.3286 | 0.162 | 0.0855 | 0.3615 | 0.8986 | 0.0833 | 0.2226 | 0.2717 | 0.2053 | 0.462 | 0.9276 | 0.3357 | 0.4836 | 0.0119 | 0.0597 |
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| 24.1639 | 6.0 | 1890 | 23.3457 | 0.1761 | 0.3319 | 0.1641 | 0.0891 | 0.3606 | 0.9016 | 0.0838 | 0.2249 | 0.267 | 0.2003 | 0.4539 | 0.9265 | 0.3412 | 0.4749 | 0.0111 | 0.059 |
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| 23.581 | 7.0 | 2205 | 23.0218 | 0.1801 | 0.3415 | 0.1687 | 0.0924 | 0.3682 | 0.9111 | 0.0854 | 0.2295 | 0.2735 | 0.2061 | 0.4619 | 0.9356 | 0.3475 | 0.4829 | 0.0126 | 0.064 |
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| 23.1336 | 8.0 | 2520 | 22.8133 | 0.1817 | 0.3458 | 0.1673 | 0.0959 | 0.3723 | 0.9122 | 0.0852 | 0.234 | 0.2782 | 0.2108 | 0.4682 | 0.9352 | 0.3507 | 0.4868 | 0.0127 | 0.0697 |
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| 22.6498 | 9.0 | 2835 | 22.8115 | 0.1823 | 0.3478 | 0.1683 | 0.0948 | 0.3758 | 0.9137 | 0.0856 | 0.2347 | 0.2818 | 0.2148 | 0.4691 | 0.9358 | 0.3508 | 0.4884 | 0.0139 | 0.0751 |
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| 22.3868 | 9.9698 | 3140 | 22.5821 | 0.181 | 0.35 | 0.164 | 0.0954 | 0.3758 | 0.9135 | 0.0856 | 0.2359 | 0.2819 | 0.2158 | 0.4688 | 0.9371 | 0.3473 | 0.4911 | 0.0147 | 0.0727 |
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### Framework versions
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- Transformers 4.50.0.dev0
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- Pytorch 2.6.0+cu124
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- Datasets 3.3.2
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- Tokenizers 0.21.0
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