---
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 qubvel-hf/ade20k-mini dataset.
It achieves the following results on the evaluation set:
- Loss: 31.0067
- Map: 0.2061
- Map 50: 0.4076
- Map 75: 0.1946
- Map Small: 0.1368
- Map Medium: 0.623
- Map Large: 0.82
- Mar 1: 0.0921
- Mar 10: 0.2488
- Mar 100: 0.2856
- Mar Small: 0.2105
- Mar Medium: 0.7164
- Mar Large: 0.8705
- Map Person: 0.1413
- Mar 100 Person: 0.2035
- Map Car: 0.2709
- Mar 100 Car: 0.3678

## 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 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: 2.0
- 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 Person | Mar 100 Person | Map Car | Mar 100 Car |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:----------:|:--------------:|:-------:|:-----------:|
| 37.3934       | 1.0   | 100  | 33.6332         | 0.1981 | 0.3956 | 0.1799 | 0.1285    | 0.6173     | 0.7992    | 0.0896 | 0.2453 | 0.2821  | 0.2074    | 0.7135     | 0.8354    | 0.1349     | 0.2001         | 0.2613  | 0.3641      |
| 29.0441       | 2.0   | 200  | 31.0067         | 0.2061 | 0.4076 | 0.1946 | 0.1368    | 0.623      | 0.82      | 0.0921 | 0.2488 | 0.2856  | 0.2105    | 0.7164     | 0.8705    | 0.1413     | 0.2035         | 0.2709  | 0.3678      |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.0+cu121
- Datasets 2.19.1
- Tokenizers 0.21.0