learning_rate: 5e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
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: cosine
num_epochs: 30

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 Raccoon	Mar 100 Raccoon
No log	1.0	40	1.8993	0.0434	0.1303	0.0182	-1.0	0.0041	0.0543	0.1565	0.3478	0.5022	-1.0	0.1286	0.5692	0.0434	0.5022
No log	2.0	80	1.8368	0.0593	0.1889	0.0201	-1.0	0.0467	0.0682	0.1457	0.3391	0.5261	-1.0	0.1286	0.5974	0.0593	0.5261
No log	3.0	120	2.0381	0.0609	0.1819	0.0157	-1.0	0.0043	0.0695	0.0978	0.3348	0.4761	-1.0	0.1429	0.5359	0.0609	0.4761
No log	4.0	160	1.9035	0.0518	0.1974	0.0136	-1.0	0.0048	0.0602	0.113	0.3304	0.5196	-1.0	0.1286	0.5897	0.0518	0.5196
No log	5.0	200	1.5900	0.1056	0.2694	0.0548	-1.0	0.1084	0.1211	0.1783	0.4696	0.5913	-1.0	0.2143	0.659	0.1056	0.5913
No log	6.0	240	1.8019	0.1041	0.3265	0.0344	-1.0	0.0217	0.1211	0.1652	0.4	0.5913	-1.0	0.2143	0.659	0.1041	0.5913
No log	7.0	280	1.6795	0.184	0.5686	0.0576	-1.0	0.0388	0.2135	0.2478	0.4261	0.6174	-1.0	0.2	0.6923	0.184	0.6174
No log	8.0	320	1.5859	0.1701	0.4806	0.0508	-1.0	0.041	0.1967	0.2109	0.4413	0.6348	-1.0	0.2714	0.7	0.1701	0.6348
No log	9.0	360	1.4233	0.1691	0.4605	0.0585	-1.0	0.0667	0.1927	0.213	0.4609	0.6957	-1.0	0.3571	0.7564	0.1691	0.6957
No log	10.0	400	1.1649	0.3707	0.7922	0.2303	-1.0	0.2315	0.4006	0.4022	0.6717	0.7413	-1.0	0.4571	0.7923	0.3707	0.7413
No log	11.0	440	1.1772	0.3995	0.7235	0.4299	-1.0	0.2656	0.4305	0.3978	0.6696	0.7783	-1.0	0.5	0.8282	0.3995	0.7783
No log	12.0	480	1.0596	0.5043	0.8137	0.6038	-1.0	0.3713	0.5363	0.5174	0.7565	0.7957	-1.0	0.5143	0.8462	0.5043	0.7957
1.1275	13.0	520	1.1353	0.46	0.8825	0.4766	-1.0	0.3399	0.4878	0.4761	0.7326	0.7826	-1.0	0.5571	0.8231	0.46	0.7826
1.1275	14.0	560	1.0947	0.5594	0.8907	0.5893	-1.0	0.4379	0.5858	0.5543	0.7391	0.8022	-1.0	0.5571	0.8462	0.5594	0.8022
1.1275	15.0	600	1.1123	0.5182	0.8104	0.5584	-1.0	0.3251	0.5541	0.5109	0.7413	0.7913	-1.0	0.5143	0.841	0.5182	0.7913
1.1275	16.0	640	0.9781	0.545	0.7859	0.6785	-1.0	0.3575	0.5923	0.55	0.737	0.7978	-1.0	0.5571	0.841	0.545	0.7978
1.1275	17.0	680	0.9527	0.5946	0.8522	0.6636	-1.0	0.4856	0.6189	0.6109	0.7783	0.813	-1.0	0.6286	0.8462	0.5946	0.813
1.1275	18.0	720	0.8526	0.6314	0.8886	0.6991	-1.0	0.5033	0.6627	0.6348	0.7848	0.8152	-1.0	0.6286	0.8487	0.6314	0.8152
1.1275	19.0	760	0.9402	0.622	0.9133	0.72	-1.0	0.5502	0.6449	0.6043	0.7674	0.8065	-1.0	0.6143	0.841	0.622	0.8065
1.1275	20.0	800	0.9228	0.6429	0.8911	0.7797	-1.0	0.5107	0.6732	0.6022	0.7478	0.7957	-1.0	0.5714	0.8359	0.6429	0.7957
1.1275	21.0	840	0.8760	0.6513	0.9153	0.8075	-1.0	0.5277	0.6811	0.6217	0.7717	0.8043	-1.0	0.5857	0.8436	0.6513	0.8043
1.1275	22.0	880	0.8393	0.664	0.9235	0.8122	-1.0	0.5793	0.687	0.6326	0.7891	0.8217	-1.0	0.6143	0.859	0.664	0.8217
1.1275	23.0	920	0.8733	0.6513	0.9207	0.8099	-1.0	0.5582	0.677	0.6196	0.7913	0.8217	-1.0	0.6286	0.8564	0.6513	0.8217
1.1275	24.0	960	0.9070	0.6408	0.9151	0.7751	-1.0	0.5287	0.6704	0.613	0.787	0.8196	-1.0	0.6143	0.8564	0.6408	0.8196
0.6623	25.0	1000	0.8701	0.6567	0.9224	0.8088	-1.0	0.5245	0.6868	0.6217	0.7848	0.8239	-1.0	0.6143	0.8615	0.6567	0.8239
0.6623	26.0	1040	0.8684	0.6547	0.918	0.7998	-1.0	0.5428	0.6821	0.6261	0.787	0.8283	-1.0	0.6429	0.8615	0.6547	0.8283
0.6623	27.0	1080	0.9054	0.6523	0.9214	0.7853	-1.0	0.5288	0.6819	0.613	0.7891	0.8196	-1.0	0.6429	0.8513	0.6523	0.8196
0.6623	28.0	1120	0.8803	0.6537	0.9146	0.7938	-1.0	0.4588	0.6901	0.6196	0.7848	0.8283	-1.0	0.6286	0.8641	0.6537	0.8283
0.6623	29.0	1160	0.8798	0.6541	0.9155	0.7967	-1.0	0.4528	0.6916	0.6152	0.7826	0.8217	-1.0	0.6	0.8615	0.6541	0.8217
0.6623	30.0	1200	0.8874	0.6541	0.9155	0.7967	-1.0	0.4528	0.6915	0.6152	0.7826	0.8217	-1.0	0.6	0.8615	0.6541	0.8217

Framework versions

Transformers 4.57.6
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2

CarlosAraEspinosa/yolo_finetuned_raccoon

yolo_finetuned_raccoon

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

CarlosAraEspinosa/
yolo_finetuned_raccoon