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---
library_name: transformers
license: other
base_model: facebook/mask2former-swin-tiny-ade-semantic
tags:
- generated_from_trainer
model-index:
- name: mask2former
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mask2former
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.
It achieves the following results on the evaluation set:
- Loss: 29.1112
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 4
- num_epochs: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 50.7018 | 0.1408 | 50 | 44.2435 |
| 40.5877 | 0.2817 | 100 | 39.6465 |
| 37.4102 | 0.4225 | 150 | 37.2471 |
| 35.7502 | 0.5634 | 200 | 36.3455 |
| 34.7067 | 0.7042 | 250 | 34.8824 |
| 34.0798 | 0.8451 | 300 | 34.8520 |
| 33.3503 | 0.9859 | 350 | 33.7321 |
| 32.3436 | 1.1268 | 400 | 33.1560 |
| 32.3845 | 1.2676 | 450 | 33.0411 |
| 30.8809 | 1.4085 | 500 | 32.7852 |
| 31.689 | 1.5493 | 550 | 31.9914 |
| 31.036 | 1.6901 | 600 | 32.7297 |
| 30.9795 | 1.8310 | 650 | 31.8848 |
| 30.7918 | 1.9718 | 700 | 31.5285 |
| 30.1432 | 2.1127 | 750 | 32.0634 |
| 29.7082 | 2.2535 | 800 | 31.1849 |
| 28.7869 | 2.3944 | 850 | 30.9022 |
| 29.4227 | 2.5352 | 900 | 30.5902 |
| 29.1865 | 2.6761 | 950 | 30.3818 |
| 29.2715 | 2.8169 | 1000 | 30.9196 |
| 29.1941 | 2.9577 | 1050 | 30.8163 |
| 28.5256 | 3.0986 | 1100 | 30.4730 |
| 28.0419 | 3.2394 | 1150 | 30.6531 |
| 28.0538 | 3.3803 | 1200 | 30.0779 |
| 27.9463 | 3.5211 | 1250 | 30.6114 |
| 27.4152 | 3.6620 | 1300 | 30.5519 |
| 27.7461 | 3.8028 | 1350 | 29.5641 |
| 27.5604 | 3.9437 | 1400 | 30.1296 |
| 27.381 | 4.0845 | 1450 | 30.5017 |
| 26.3816 | 4.2254 | 1500 | 29.6898 |
| 26.5218 | 4.3662 | 1550 | 29.9475 |
| 26.9798 | 4.5070 | 1600 | 29.3323 |
| 26.8186 | 4.6479 | 1650 | 29.5755 |
| 27.5111 | 4.7887 | 1700 | 30.7945 |
| 27.0839 | 4.9296 | 1750 | 29.4147 |
| 26.6393 | 5.0704 | 1800 | 28.7983 |
| 26.3564 | 5.2113 | 1850 | 29.2245 |
| 25.6174 | 5.3521 | 1900 | 28.9337 |
| 25.8777 | 5.4930 | 1950 | 29.4778 |
| 25.6848 | 5.6338 | 2000 | 28.4992 |
| 26.4625 | 5.7746 | 2050 | 29.6182 |
| 26.8448 | 5.9155 | 2100 | 29.5377 |
| 26.0681 | 6.0563 | 2150 | 29.2390 |
| 25.628 | 6.1972 | 2200 | 29.1112 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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