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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-ade-semantic |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: 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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# mask2former |
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This model is a fine-tuned version of [facebook/mask2former-swin-tiny-ade-semantic](https://huggingface.co/facebook/mask2former-swin-tiny-ade-semantic) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 29.1112 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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_steps: 4 |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 50.7018 | 0.1408 | 50 | 44.2435 | |
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| 40.5877 | 0.2817 | 100 | 39.6465 | |
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| 37.4102 | 0.4225 | 150 | 37.2471 | |
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| 35.7502 | 0.5634 | 200 | 36.3455 | |
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| 34.7067 | 0.7042 | 250 | 34.8824 | |
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| 34.0798 | 0.8451 | 300 | 34.8520 | |
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| 33.3503 | 0.9859 | 350 | 33.7321 | |
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| 32.3436 | 1.1268 | 400 | 33.1560 | |
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| 32.3845 | 1.2676 | 450 | 33.0411 | |
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| 30.8809 | 1.4085 | 500 | 32.7852 | |
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| 31.689 | 1.5493 | 550 | 31.9914 | |
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| 31.036 | 1.6901 | 600 | 32.7297 | |
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| 30.9795 | 1.8310 | 650 | 31.8848 | |
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| 30.7918 | 1.9718 | 700 | 31.5285 | |
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| 30.1432 | 2.1127 | 750 | 32.0634 | |
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| 29.7082 | 2.2535 | 800 | 31.1849 | |
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| 28.7869 | 2.3944 | 850 | 30.9022 | |
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| 29.4227 | 2.5352 | 900 | 30.5902 | |
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| 29.1865 | 2.6761 | 950 | 30.3818 | |
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| 29.2715 | 2.8169 | 1000 | 30.9196 | |
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| 29.1941 | 2.9577 | 1050 | 30.8163 | |
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| 28.5256 | 3.0986 | 1100 | 30.4730 | |
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| 28.0419 | 3.2394 | 1150 | 30.6531 | |
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| 28.0538 | 3.3803 | 1200 | 30.0779 | |
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| 27.9463 | 3.5211 | 1250 | 30.6114 | |
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| 27.4152 | 3.6620 | 1300 | 30.5519 | |
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| 27.7461 | 3.8028 | 1350 | 29.5641 | |
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| 27.5604 | 3.9437 | 1400 | 30.1296 | |
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| 27.381 | 4.0845 | 1450 | 30.5017 | |
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| 26.3816 | 4.2254 | 1500 | 29.6898 | |
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| 26.5218 | 4.3662 | 1550 | 29.9475 | |
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| 26.9798 | 4.5070 | 1600 | 29.3323 | |
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| 26.8186 | 4.6479 | 1650 | 29.5755 | |
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| 27.5111 | 4.7887 | 1700 | 30.7945 | |
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| 27.0839 | 4.9296 | 1750 | 29.4147 | |
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| 26.6393 | 5.0704 | 1800 | 28.7983 | |
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| 26.3564 | 5.2113 | 1850 | 29.2245 | |
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| 25.6174 | 5.3521 | 1900 | 28.9337 | |
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| 25.8777 | 5.4930 | 1950 | 29.4778 | |
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| 25.6848 | 5.6338 | 2000 | 28.4992 | |
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| 26.4625 | 5.7746 | 2050 | 29.6182 | |
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| 26.8448 | 5.9155 | 2100 | 29.5377 | |
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| 26.0681 | 6.0563 | 2150 | 29.2390 | |
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| 25.628 | 6.1972 | 2200 | 29.1112 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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