---
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_backbone_frozen_1
  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_backbone_frozen_1

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: 22.5821
- Map: 0.181
- Map 50: 0.35
- Map 75: 0.164
- Map Small: 0.0954
- Map Medium: 0.3758
- Map Large: 0.9135
- Mar 1: 0.0856
- Mar 10: 0.2359
- Mar 100: 0.2819
- Mar Small: 0.2158
- Mar Medium: 0.4688
- Mar Large: 0.9371
- Map Car: 0.3473
- Mar 100 Car: 0.4911
- Map Person: 0.0147
- Mar 100 Person: 0.0727

## 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 |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:-------:|:-----------:|:----------:|:--------------:|
| 36.0195       | 1.0    | 315  | 27.1721         | 0.1432 | 0.279  | 0.1349 | 0.0688    | 0.3117     | 0.8516    | 0.0714 | 0.1887 | 0.2291  | 0.1605    | 0.4115     | 0.9133    | 0.2849  | 0.4372      | 0.0014     | 0.0209         |
| 28.6156       | 2.0    | 630  | 25.2879         | 0.1597 | 0.2996 | 0.1521 | 0.0779    | 0.337      | 0.8789    | 0.078  | 0.2055 | 0.2497  | 0.1825    | 0.4386     | 0.9173    | 0.3147  | 0.4628      | 0.0046     | 0.0367         |
| 26.5961       | 3.0    | 945  | 24.4641         | 0.1679 | 0.3171 | 0.1572 | 0.0817    | 0.3481     | 0.8921    | 0.0809 | 0.2137 | 0.259   | 0.193     | 0.4441     | 0.9229    | 0.326   | 0.473       | 0.0098     | 0.045          |
| 25.435        | 4.0    | 1260 | 24.1017         | 0.1701 | 0.3217 | 0.1577 | 0.0815    | 0.3562     | 0.9002    | 0.0816 | 0.2169 | 0.2601  | 0.1929    | 0.4479     | 0.9272    | 0.329   | 0.469       | 0.0112     | 0.0512         |
| 24.7221       | 5.0    | 1575 | 23.5551         | 0.1738 | 0.3286 | 0.162  | 0.0855    | 0.3615     | 0.8986    | 0.0833 | 0.2226 | 0.2717  | 0.2053    | 0.462      | 0.9276    | 0.3357  | 0.4836      | 0.0119     | 0.0597         |
| 24.1639       | 6.0    | 1890 | 23.3457         | 0.1761 | 0.3319 | 0.1641 | 0.0891    | 0.3606     | 0.9016    | 0.0838 | 0.2249 | 0.267   | 0.2003    | 0.4539     | 0.9265    | 0.3412  | 0.4749      | 0.0111     | 0.059          |
| 23.581        | 7.0    | 2205 | 23.0218         | 0.1801 | 0.3415 | 0.1687 | 0.0924    | 0.3682     | 0.9111    | 0.0854 | 0.2295 | 0.2735  | 0.2061    | 0.4619     | 0.9356    | 0.3475  | 0.4829      | 0.0126     | 0.064          |
| 23.1336       | 8.0    | 2520 | 22.8133         | 0.1817 | 0.3458 | 0.1673 | 0.0959    | 0.3723     | 0.9122    | 0.0852 | 0.234  | 0.2782  | 0.2108    | 0.4682     | 0.9352    | 0.3507  | 0.4868      | 0.0127     | 0.0697         |
| 22.6498       | 9.0    | 2835 | 22.8115         | 0.1823 | 0.3478 | 0.1683 | 0.0948    | 0.3758     | 0.9137    | 0.0856 | 0.2347 | 0.2818  | 0.2148    | 0.4691     | 0.9358    | 0.3508  | 0.4884      | 0.0139     | 0.0751         |
| 22.3868       | 9.9698 | 3140 | 22.5821         | 0.181  | 0.35   | 0.164  | 0.0954    | 0.3758     | 0.9135    | 0.0856 | 0.2359 | 0.2819  | 0.2158    | 0.4688     | 0.9371    | 0.3473  | 0.4911      | 0.0147     | 0.0727         |


### Framework versions

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