metadata
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-posture
results: []
finetune-instance-segmentation-posture
This model is a fine-tuned version of facebook/mask2former-swin-tiny-coco-instance on the qubvel-hf/ade20k-mini dataset. It achieves the following results on the evaluation set:
- Loss: 30.5625
- Map: 0.2089
- Map 50: 0.4081
- Map 75: 0.1963
- Map Small: 0.1412
- Map Medium: 0.6277
- Map Large: 0.8115
- Mar 1: 0.0944
- Mar 10: 0.25
- Mar 100: 0.2879
- Mar Small: 0.2137
- Mar Medium: 0.7147
- Mar Large: 0.8531
- Map Person: 0.1381
- Mar 100 Person: 0.2036
- Map Car: 0.2797
- Mar 100 Car: 0.3722
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
34.1337 | 1.0 | 100 | 32.3431 | 0.1958 | 0.3913 | 0.181 | 0.1319 | 0.6051 | 0.7775 | 0.0924 | 0.2465 | 0.2845 | 0.2104 | 0.7094 | 0.8587 | 0.1243 | 0.2001 | 0.2673 | 0.3689 |
28.4514 | 2.0 | 200 | 30.5625 | 0.2089 | 0.4081 | 0.1963 | 0.1412 | 0.6277 | 0.8115 | 0.0944 | 0.25 | 0.2879 | 0.2137 | 0.7147 | 0.8531 | 0.1381 | 0.2036 | 0.2797 | 0.3722 |
Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1