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---
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
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