learning_rate: 5e-05
train_batch_size: 16
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
1.0185	1.0	10	0.8201	0.1605	0.2363	0.1872	-1.0	0.4596	0.186	0.4705	0.7523	0.8409	-1.0	0.8	0.8439	0.1605	0.8409
0.8203	2.0	20	0.8318	0.2987	0.4315	0.3349	-1.0	0.3974	0.3219	0.6182	0.7818	0.8273	-1.0	0.8	0.8293	0.2987	0.8273
0.7627	3.0	30	0.8670	0.5198	0.7492	0.5722	-1.0	0.5006	0.5348	0.6091	0.7682	0.8114	-1.0	0.7333	0.8171	0.5198	0.8114
0.7001	4.0	40	0.8055	0.5695	0.7849	0.6403	-1.0	0.3961	0.5871	0.6159	0.7864	0.8318	-1.0	0.6667	0.8439	0.5695	0.8318
0.7055	5.0	50	0.8247	0.5994	0.8726	0.6319	-1.0	0.2619	0.6208	0.6068	0.7705	0.8318	-1.0	0.7	0.8415	0.5994	0.8318
0.6666	6.0	60	0.8543	0.611	0.8801	0.6593	-1.0	0.2743	0.6346	0.625	0.7591	0.8114	-1.0	0.6667	0.822	0.611	0.8114
0.6805	7.0	70	0.7926	0.6629	0.9575	0.7264	-1.0	0.3727	0.7009	0.6545	0.7932	0.8318	-1.0	0.6667	0.8439	0.6629	0.8318
0.6634	8.0	80	0.7975	0.6286	0.9051	0.6973	-1.0	0.3919	0.6781	0.6614	0.7864	0.8136	-1.0	0.6667	0.8244	0.6286	0.8136
0.5842	9.0	90	0.7745	0.6702	0.9514	0.7409	-1.0	0.3815	0.7084	0.6455	0.8068	0.8386	-1.0	0.7	0.8488	0.6702	0.8386
0.5782	10.0	100	0.7431	0.6992	0.9344	0.7459	-1.0	0.3699	0.7306	0.6682	0.8091	0.8295	-1.0	0.6667	0.8415	0.6992	0.8295
0.5481	11.0	110	0.7558	0.7045	0.9432	0.8266	-1.0	0.4334	0.7297	0.6614	0.7977	0.8273	-1.0	0.7333	0.8341	0.7045	0.8273
0.5646	12.0	120	0.7294	0.6898	0.9318	0.7457	-1.0	0.4016	0.7233	0.6636	0.8227	0.8386	-1.0	0.7	0.8488	0.6898	0.8386
0.5103	13.0	130	0.7274	0.7119	0.9541	0.7887	-1.0	0.3485	0.7481	0.6705	0.8182	0.85	-1.0	0.7333	0.8585	0.7119	0.85
0.4871	14.0	140	0.6940	0.7183	0.9593	0.7849	-1.0	0.4254	0.7509	0.6727	0.8182	0.8386	-1.0	0.7	0.8488	0.7183	0.8386
0.5014	15.0	150	0.7047	0.7275	0.9632	0.7937	-1.0	0.4432	0.7569	0.6909	0.8159	0.8455	-1.0	0.7333	0.8537	0.7275	0.8455
0.4533	16.0	160	0.6699	0.7273	0.9577	0.8205	-1.0	0.4339	0.7599	0.675	0.825	0.8545	-1.0	0.7333	0.8634	0.7273	0.8545
0.4623	17.0	170	0.7027	0.7253	0.9607	0.8059	-1.0	0.5453	0.7539	0.7045	0.8227	0.85	-1.0	0.7	0.861	0.7253	0.85
0.4345	18.0	180	0.7005	0.7158	0.9594	0.8005	-1.0	0.442	0.7412	0.675	0.8114	0.8409	-1.0	0.7333	0.8488	0.7158	0.8409
0.4538	19.0	190	0.7192	0.722	0.9619	0.7999	-1.0	0.4359	0.7494	0.6773	0.8136	0.8432	-1.0	0.7333	0.8512	0.722	0.8432
0.4298	20.0	200	0.7308	0.7033	0.9566	0.7983	-1.0	0.479	0.7243	0.6727	0.8045	0.8386	-1.0	0.7667	0.8439	0.7033	0.8386
0.388	21.0	210	0.7473	0.7125	0.9608	0.8134	-1.0	0.4756	0.7344	0.675	0.8091	0.8455	-1.0	0.7333	0.8537	0.7125	0.8455
0.3752	22.0	220	0.7255	0.7184	0.9599	0.8072	-1.0	0.49	0.7406	0.675	0.8182	0.8477	-1.0	0.7667	0.8537	0.7184	0.8477
0.3757	23.0	230	0.7274	0.7227	0.9609	0.8077	-1.0	0.4702	0.7482	0.6773	0.8136	0.8455	-1.0	0.7667	0.8512	0.7227	0.8455
0.3856	24.0	240	0.7218	0.7194	0.962	0.807	-1.0	0.5258	0.7444	0.6727	0.8159	0.8477	-1.0	0.7333	0.8561	0.7194	0.8477
0.3609	25.0	250	0.7184	0.7205	0.959	0.8131	-1.0	0.486	0.7448	0.6955	0.8136	0.8455	-1.0	0.7	0.8561	0.7205	0.8455
0.3491	26.0	260	0.7056	0.7237	0.957	0.7906	-1.0	0.4863	0.749	0.675	0.8205	0.8545	-1.0	0.7333	0.8634	0.7237	0.8545
0.3244	27.0	270	0.7156	0.7229	0.9586	0.7905	-1.0	0.4368	0.7498	0.675	0.8182	0.8545	-1.0	0.7333	0.8634	0.7229	0.8545
0.3524	28.0	280	0.7156	0.7234	0.9594	0.7907	-1.0	0.4368	0.7509	0.675	0.8205	0.8523	-1.0	0.7333	0.861	0.7234	0.8523
0.341	29.0	290	0.7152	0.7239	0.9594	0.7922	-1.0	0.437	0.7507	0.675	0.8205	0.8545	-1.0	0.7667	0.861	0.7239	0.8545
0.3643	30.0	300	0.7152	0.7239	0.9594	0.7919	-1.0	0.437	0.7509	0.675	0.8205	0.8545	-1.0	0.7667	0.861	0.7239	0.8545

Framework versions

Transformers 4.57.6
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2

Yagofue/yolo_finetuned_raccoon

yolo_finetuned_raccoon

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Yagofue/
yolo_finetuned_raccoon