DeTr-TableDetection-5000-images

This model is a fine-tuned version of facebook/detr-resnet-50 on the table_detection_light dataset. It achieves the following results on the evaluation set:

• Loss: 0.3184
• Mean Iou: 0.0234

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: 5e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou
0.741	1.0	313	0.7054	0.0259
0.5559	2.0	626	0.5159	0.0231
0.4213	3.0	939	0.4154	0.0254
0.4374	4.0	1252	0.4072	0.0249
0.3884	5.0	1565	0.4454	0.0232
0.4057	6.0	1878	0.4251	0.0249
0.3511	7.0	2191	0.3882	0.0239
0.3463	8.0	2504	0.3766	0.0243
0.3346	9.0	2817	0.4142	0.0236
0.3183	10.0	3130	0.3804	0.0242
0.3049	11.0	3443	0.3642	0.0244
0.2942	12.0	3756	0.3541	0.0253
0.2836	13.0	4069	0.3359	0.0252
0.2738	14.0	4382	0.3338	0.0254
0.2629	15.0	4695	0.3318	0.0267
0.2591	16.0	5008	0.3311	0.0224
0.2457	17.0	5321	0.3317	0.0234
0.2406	18.0	5634	0.3219	0.0238
0.2383	19.0	5947	0.3143	0.0238
0.2229	20.0	6260	0.3184	0.0234

Framework versions

• Transformers 4.26.0
• Pytorch 1.13.1+cu117
• Datasets 2.5.1
• Tokenizers 0.13.2