detr-resnet-50_fine_tuned_loc-2023

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

• Loss: 0.8784

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss
3.731	0.16	50	2.6356
2.4875	0.31	100	2.2348
2.1786	0.47	150	2.1148
1.9845	0.62	200	1.8847
1.8507	0.78	250	1.8331
1.6813	0.94	300	1.5620
1.5613	1.09	350	1.5898
1.4966	1.25	400	1.4161
1.4831	1.41	450	1.4831
1.4587	1.56	500	1.3218
1.433	1.72	550	1.3529
1.33	1.88	600	1.2453
1.2842	2.03	650	1.2956
1.2807	2.19	700	1.1993
1.1767	2.34	750	1.1557
1.2134	2.5	800	1.1393
1.1897	2.66	850	1.2016
1.1784	2.81	900	1.1235
1.2016	2.97	950	1.1378
1.06	3.12	1000	1.0803
1.1124	3.28	1050	1.1145
1.1191	3.44	1100	1.0523
1.0819	3.59	1150	1.0165
1.1196	3.75	1200	1.0349
1.0534	3.91	1250	1.0441
1.0365	4.06	1300	1.1177
0.9853	4.22	1350	1.0721
0.9984	4.38	1400	0.9923
0.9802	4.53	1450	1.0079
1.04	4.69	1500	1.0198
1.098	4.84	1550	0.9788
1.079	5.0	1600	1.0291
1.0664	5.16	1650	0.9691
0.9715	5.31	1700	0.9380
0.9723	5.47	1750	1.0164
1.0019	5.62	1800	1.0064
0.9895	5.78	1850	1.0364
0.9835	5.94	1900	0.9848
0.994	6.09	1950	0.9353
0.9693	6.25	2000	0.9425
0.9413	6.41	2050	0.9173
0.9375	6.56	2100	0.9663
0.952	6.72	2150	0.8951
0.8927	6.88	2200	0.9099
0.8777	7.03	2250	0.9238
0.8976	7.19	2300	0.9715
0.9451	7.34	2350	0.9373
0.8972	7.5	2400	0.8959
0.9393	7.66	2450	1.0062
0.9	7.81	2500	0.8920
0.915	7.97	2550	0.8833
0.9018	8.12	2600	0.8671
0.8272	8.28	2650	0.9304
0.943	8.44	2700	0.8593
0.8667	8.59	2750	0.8875
0.871	8.75	2800	0.8457
0.9023	8.91	2850	0.8448
0.8733	9.06	2900	0.8261
0.8686	9.22	2950	0.8489
0.8412	9.38	3000	0.8244
0.8385	9.53	3050	0.8830
0.891	9.69	3100	0.8349
0.8692	9.84	3150	0.8672
0.8247	10.0	3200	0.8811
0.799	10.16	3250	0.8784

Framework versions

• Transformers 4.27.4
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.3