---
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