Model save

README.md

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+---
+library_name: transformers
+license: other
+base_model: facebook/mask2former-swin-tiny-coco-instance
+tags:
+- 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 an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 28.4481
+- Map: 0.2172
+- Map 50: 0.4234
+- Map 75: 0.2041
+- Map Small: 0.1458
+- Map Medium: 0.6353
+- Map Large: 0.8076
+- Mar 1: 0.0953
+- Mar 10: 0.254
+- Mar 100: 0.2903
+- Mar Small: 0.2169
+- Mar Medium: 0.7113
+- Mar Large: 0.8594
+- Map Person: 0.1476
+- Mar 100 Person: 0.205
+- Map Car: 0.2867
+- Mar 100 Car: 0.3755
+
+## 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: 4.0
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:----------:|:--------------:|:-------:|:-----------:|
+| 33.5412       | 1.0   | 100  | 31.5328         | 0.1929 | 0.3918 | 0.1737 | 0.1281    | 0.6122     | 0.7895    | 0.0904 | 0.2473 | 0.2836  | 0.2105    | 0.7063     | 0.8229    | 0.13       | 0.2001         | 0.2558  | 0.3672      |
+| 27.9471       | 2.0   | 200  | 29.7181         | 0.2053 | 0.4151 | 0.1851 | 0.1387    | 0.6192     | 0.8018    | 0.093  | 0.2507 | 0.2872  | 0.2142    | 0.7079     | 0.8323    | 0.1364     | 0.2029         | 0.2741  | 0.3714      |
+| 26.4855       | 3.0   | 300  | 28.9786         | 0.2134 | 0.4219 | 0.1945 | 0.1451    | 0.6255     | 0.8047    | 0.0944 | 0.2543 | 0.2918  | 0.2198    | 0.7045     | 0.8594    | 0.143      | 0.2059         | 0.2837  | 0.3777      |
+| 25.4746       | 4.0   | 400  | 28.4481         | 0.2172 | 0.4234 | 0.2041 | 0.1458    | 0.6353     | 0.8076    | 0.0953 | 0.254  | 0.2903  | 0.2169    | 0.7113     | 0.8594    | 0.1476     | 0.205          | 0.2867  | 0.3755      |
+
+
+### Framework versions
+
+- Transformers 4.48.0.dev0
+- Pytorch 2.5.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.21.0