---
library_name: transformers
license: other
base_model: facebook/mask2former-swin-tiny-coco-instance
tags:
- image-segmentation
- instance-segmentation
- vision
- generated_from_trainer
model-index:
- name: finetune-instance-segmentation-ade20k-mini-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. -->

# finetune-instance-segmentation-ade20k-mini-mask2former

This model is a fine-tuned version of [facebook/mask2former-swin-tiny-coco-instance](https://huggingface.co/facebook/mask2former-swin-tiny-coco-instance) on the yeray142/kitti-mots-instance dataset.
It achieves the following results on the evaluation set:
- Loss: 21.4682
- Map: 0.2191
- Map 50: 0.4214
- Map 75: 0.2032
- Map Small: 0.1293
- Map Medium: 0.4299
- Map Large: 0.9458
- Mar 1: 0.0979
- Mar 10: 0.2731
- Mar 100: 0.3209
- Mar Small: 0.2542
- Mar Medium: 0.5212
- Mar Large: 0.9604
- Map Car: 0.406
- Mar 100 Car: 0.5312
- Map Person: 0.0323
- Mar 100 Person: 0.1106

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: constant
- num_epochs: 10.0
- mixed_precision_training: Native AMP

### Training results

| 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 |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:-------:|:-----------:|:----------:|:--------------:|
| 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         |
| 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         |
| 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         |
| 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         |
| 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         |
| 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         |
| 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         |
| 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         |
| 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         |
| 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         |


### Framework versions

- Transformers 4.50.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0