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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
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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
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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: 21.4682
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- Map: 0.2191
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- Map 50: 0.4214
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- Map 75: 0.2032
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- Map Small: 0.1293
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- Map Medium: 0.4299
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- Map Large: 0.9458
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- Mar 1: 0.0979
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- Mar 10: 0.2731
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- Mar 100: 0.3209
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- Mar Small: 0.2542
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- Mar Medium: 0.5212
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- Mar Large: 0.9604
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- Map Car: 0.406
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- Mar 100 Car: 0.5312
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- Map Person: 0.0323
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- Mar 100 Person: 0.1106
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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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| 32.2084 | 1.0 | 315 | 24.9517 | 0.1754 | 0.3241 | 0.1688 | 0.0901 | 0.3559 | 0.9036 | 0.0848 | 0.2249 | 0.2625 | 0.1937 | 0.4585 | 0.9383 | 0.3414 | 0.4833 | 0.0093 | 0.0417 |
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| 26.4262 | 2.0 | 630 | 23.8438 | 0.1907 | 0.358 | 0.1793 | 0.1022 | 0.3764 | 0.9182 | 0.0904 | 0.2378 | 0.2851 | 0.2184 | 0.4779 | 0.9446 | 0.3657 | 0.5024 | 0.0157 | 0.0677 |
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| 24.7264 | 3.0 | 945 | 22.7357 | 0.197 | 0.3715 | 0.189 | 0.1086 | 0.3803 | 0.9337 | 0.0912 | 0.2441 | 0.2901 | 0.2234 | 0.4819 | 0.9531 | 0.3769 | 0.5086 | 0.017 | 0.0716 |
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| 23.7704 | 4.0 | 1260 | 22.5427 | 0.2001 | 0.3753 | 0.1878 | 0.1092 | 0.3902 | 0.9368 | 0.0924 | 0.2519 | 0.2994 | 0.2332 | 0.4914 | 0.9552 | 0.3791 | 0.513 | 0.0211 | 0.0858 |
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| 22.7954 | 5.0 | 1575 | 22.0928 | 0.2071 | 0.3926 | 0.195 | 0.1184 | 0.4043 | 0.933 | 0.0961 | 0.2594 | 0.3075 | 0.2418 | 0.5028 | 0.9524 | 0.3906 | 0.5253 | 0.0237 | 0.0897 |
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| 22.2719 | 6.0 | 1890 | 21.8539 | 0.2135 | 0.4034 | 0.1965 | 0.1216 | 0.4159 | 0.9446 | 0.0973 | 0.265 | 0.3128 | 0.2478 | 0.5031 | 0.9608 | 0.3985 | 0.5309 | 0.0285 | 0.0946 |
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| 21.6338 | 7.0 | 2205 | 21.7856 | 0.2125 | 0.4048 | 0.1965 | 0.1201 | 0.4207 | 0.9388 | 0.0967 | 0.2641 | 0.3131 | 0.2466 | 0.5119 | 0.957 | 0.3956 | 0.524 | 0.0293 | 0.1023 |
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| 21.3044 | 8.0 | 2520 | 21.4704 | 0.2152 | 0.4046 | 0.2003 | 0.1229 | 0.4233 | 0.9421 | 0.0983 | 0.2663 | 0.3149 | 0.2487 | 0.5109 | 0.9592 | 0.4002 | 0.5274 | 0.0301 | 0.1024 |
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| 20.9003 | 9.0 | 2835 | 21.5561 | 0.2151 | 0.4079 | 0.1994 | 0.124 | 0.4264 | 0.946 | 0.0977 | 0.2678 | 0.3194 | 0.2535 | 0.5132 | 0.9598 | 0.3997 | 0.5286 | 0.0304 | 0.1102 |
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| 20.5867 | 9.9698 | 3140 | 21.4682 | 0.2191 | 0.4214 | 0.2032 | 0.1293 | 0.4299 | 0.9458 | 0.0979 | 0.2731 | 0.3209 | 0.2542 | 0.5212 | 0.9604 | 0.406 | 0.5312 | 0.0323 | 0.1106 |
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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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