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benjamintli/
dfine-xl_sku110k

Name: dfine-xl_sku110k
Rating: 2.5 (63 reviews)

generated_from_trainer

ustc-community/dfine-xlarge-obj365

finetune

apache-2.0

endpoints_compatible

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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

benjamintli/dfine-xl_sku110k

dfine-xl_sku110k

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

benjamintli/
dfine-xl_sku110k