chickens-60

This model is a fine-tuned version of facebook/detr-resnet-50 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2476

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: 2
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• num_epochs: 60

Training results

Training Loss	Epoch	Step	Validation Loss
1.2826	1.0	497	1.1718
1.0565	2.0	994	0.9496
0.8699	3.0	1491	0.8140
0.9199	4.0	1988	0.7631
0.7011	5.0	2485	0.6355
0.7246	6.0	2982	0.6444
0.5952	7.0	3479	0.5118
0.5584	8.0	3976	0.4591
0.4884	9.0	4473	0.4302
0.4804	10.0	4970	0.4176
0.4511	11.0	5467	0.3914
0.4124	12.0	5964	0.3830
0.4182	13.0	6461	0.3754
0.4103	14.0	6958	0.3583
0.4037	15.0	7455	0.3451
0.3983	16.0	7952	0.3453
0.3606	17.0	8449	0.3426
0.3885	18.0	8946	0.3436
0.3713	19.0	9443	0.3321
0.339	20.0	9940	0.3199
0.3345	21.0	10437	0.3119
0.3215	22.0	10934	0.3189
0.353	23.0	11431	0.3031
0.338	24.0	11928	0.3152
0.3183	25.0	12425	0.3113
0.3219	26.0	12922	0.2882
0.3128	27.0	13419	0.2872
0.3032	28.0	13916	0.2876
0.3129	29.0	14413	0.2835
0.3062	30.0	14910	0.2832
0.3214	31.0	15407	0.2668
0.2891	32.0	15904	0.2838
0.297	33.0	16401	0.2756
0.296	34.0	16898	0.2753
0.2882	35.0	17395	0.2706
0.2704	36.0	17892	0.2644
0.2709	37.0	18389	0.2643
0.2852	38.0	18886	0.2640
0.259	39.0	19383	0.2698
0.276	40.0	19880	0.2602
0.2867	41.0	20377	0.2499
0.2986	42.0	20874	0.2672
0.2577	43.0	21371	0.2577
0.2583	44.0	21868	0.2487
0.2599	45.0	22365	0.2570
0.2498	46.0	22862	0.2529
0.2496	47.0	23359	0.2522
0.2596	48.0	23856	0.2568
0.2352	49.0	24353	0.2525
0.2552	50.0	24850	0.2452
0.2428	51.0	25347	0.2496
0.2538	52.0	25844	0.2483
0.2657	53.0	26341	0.2510
0.2532	54.0	26838	0.2510
0.2412	55.0	27335	0.2485
0.2822	56.0	27832	0.2491
0.2694	57.0	28329	0.2482
0.249	58.0	28826	0.2479
0.2408	59.0	29323	0.2477
0.2345	60.0	29820	0.2476

Framework versions

• Transformers 4.45.2
• Pytorch 2.4.1+cu121
• Datasets 2.19.2
• Tokenizers 0.20.0