dfine-xl_sku110k
This model is a fine-tuned version of ustc-community/dfine-xlarge-obj365 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3555
- Map: 0.2955
- Map 50: 0.4836
- Map 75: 0.3305
- Map Small: 0.1282
- Map Medium: 0.339
- Map Large: 0.2481
- Mar 1: 0.0027
- Mar 10: 0.0365
- Mar 100: 0.3884
- Mar Small: 0.1743
- Mar Medium: 0.4291
- Mar Large: 0.4861
- Map Object: 0.2955
- Mar 100 Object: 0.3884
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1
- 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 Object | Mar 100 Object |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 24.8322 | 1.0 | 1028 | 2.3555 | 0.2955 | 0.4836 | 0.3305 | 0.1282 | 0.339 | 0.2481 | 0.0027 | 0.0365 | 0.3884 | 0.1743 | 0.4291 | 0.4861 | 0.2955 | 0.3884 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.5.0
- Tokenizers 0.22.2