car_identified_model_12

This model is a fine-tuned version of apple/mobilevit-small on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.5062
• F1: 0.9130
• Roc Auc: 0.9167
• Accuracy: 0.75

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 300

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.2599	1.0	1	0.6888	0.4211	0.5417	0.0
0.2599	2.0	2	0.6888	0.3590	0.4792	0.0
0.2599	3.0	4	0.6878	0.4103	0.5208	0.0
0.2599	4.0	5	0.6872	0.45	0.5417	0.0
0.2599	5.0	6	0.6864	0.5116	0.5625	0.0
0.2599	6.0	8	0.6843	0.5238	0.5833	0.0833
0.2599	7.0	9	0.6828	0.5581	0.6042	0.1667
0.2599	8.0	10	0.6813	0.5238	0.5833	0.0833
0.2599	9.0	11	0.6803	0.45	0.5417	0.0833
0.2599	10.0	12	0.6794	0.4615	0.5625	0.0833
0.2599	11.0	14	0.6771	0.5128	0.6042	0.0833
0.2599	12.0	15	0.6762	0.5854	0.6458	0.0833
0.2599	13.0	16	0.6751	0.6341	0.6875	0.25
0.2599	14.0	18	0.6731	0.6667	0.7083	0.25
0.2599	15.0	19	0.6721	0.7273	0.75	0.3333
0.2599	16.0	20	0.6710	0.7273	0.75	0.3333
0.2599	17.0	21	0.6698	0.7273	0.75	0.3333
0.2599	18.0	22	0.6690	0.7273	0.75	0.3333
0.2599	19.0	24	0.6668	0.7273	0.75	0.3333
0.2599	20.0	25	0.6658	0.7273	0.75	0.3333
0.2599	21.0	26	0.6654	0.7273	0.75	0.3333
0.2599	22.0	28	0.6631	0.7273	0.75	0.3333
0.2599	23.0	29	0.6620	0.7273	0.75	0.3333
0.2599	24.0	30	0.6613	0.7273	0.75	0.3333
0.2599	25.0	31	0.6601	0.7273	0.75	0.3333
0.2599	26.0	32	0.6590	0.7273	0.75	0.3333
0.2599	27.0	34	0.6567	0.7273	0.75	0.3333
0.2599	28.0	35	0.6554	0.7273	0.75	0.3333
0.2599	29.0	36	0.6545	0.7273	0.75	0.3333
0.2599	30.0	38	0.6522	0.7273	0.75	0.3333
0.2599	31.0	39	0.6510	0.7273	0.75	0.3333
0.2599	32.0	40	0.6496	0.7273	0.75	0.3333
0.2599	33.0	41	0.6485	0.7273	0.75	0.3333
0.2599	34.0	42	0.6476	0.7273	0.75	0.3333
0.2599	35.0	44	0.6456	0.7273	0.75	0.3333
0.2599	36.0	45	0.6448	0.7556	0.7708	0.3333
0.2599	37.0	46	0.6437	0.7556	0.7708	0.3333
0.2599	38.0	48	0.6418	0.7727	0.7917	0.4167
0.2599	39.0	49	0.6410	0.7727	0.7917	0.4167
0.2599	40.0	50	0.6402	0.7727	0.7917	0.4167
0.2599	41.0	51	0.6392	0.7727	0.7917	0.4167
0.2599	42.0	52	0.6380	0.7907	0.8125	0.5
0.2599	43.0	54	0.6357	0.8182	0.8333	0.5833
0.2599	44.0	55	0.6349	0.8182	0.8333	0.5833
0.2599	45.0	56	0.6334	0.8000	0.8125	0.5
0.2599	46.0	58	0.6313	0.8000	0.8125	0.5
0.2599	47.0	59	0.6312	0.8000	0.8125	0.5
0.2599	48.0	60	0.6302	0.8182	0.8333	0.5833
0.2599	49.0	61	0.6291	0.8182	0.8333	0.5833
0.2599	50.0	62	0.6279	0.8182	0.8333	0.5833
0.2599	51.0	64	0.6254	0.8444	0.8542	0.6667
0.2599	52.0	65	0.6241	0.8696	0.875	0.6667
0.2599	53.0	66	0.6230	0.8696	0.875	0.6667
0.2599	54.0	68	0.6210	0.8936	0.8958	0.6667
0.2599	55.0	69	0.6200	0.9130	0.9167	0.75
0.2599	56.0	70	0.6192	0.9130	0.9167	0.75
0.2599	57.0	71	0.6175	0.8696	0.875	0.6667
0.2599	58.0	72	0.6171	0.9130	0.9167	0.75
0.2599	59.0	74	0.6157	0.9130	0.9167	0.75
0.2599	60.0	75	0.6147	0.9130	0.9167	0.75
0.2599	61.0	76	0.6140	0.9130	0.9167	0.75
0.2599	62.0	78	0.6120	0.9130	0.9167	0.75
0.2599	63.0	79	0.6107	0.9130	0.9167	0.75
0.2599	64.0	80	0.6088	0.8889	0.8958	0.6667
0.2599	65.0	81	0.6083	0.8889	0.8958	0.6667
0.2599	66.0	82	0.6076	0.9130	0.9167	0.75
0.2599	67.0	84	0.6058	0.9130	0.9167	0.75
0.2599	68.0	85	0.6042	0.9130	0.9167	0.75
0.2599	69.0	86	0.6034	0.9130	0.9167	0.75
0.2599	70.0	88	0.6017	0.9130	0.9167	0.75
0.2599	71.0	89	0.6001	0.9130	0.9167	0.75
0.2599	72.0	90	0.5998	0.9130	0.9167	0.75
0.2599	73.0	91	0.5993	0.9130	0.9167	0.75
0.2599	74.0	92	0.5985	0.9130	0.9167	0.75
0.2599	75.0	94	0.5949	0.9130	0.9167	0.75
0.2599	76.0	95	0.5938	0.9130	0.9167	0.75
0.2599	77.0	96	0.5941	0.9130	0.9167	0.75
0.2599	78.0	98	0.5925	0.9130	0.9167	0.75
0.2599	79.0	99	0.5922	0.9130	0.9167	0.75
0.2599	80.0	100	0.5911	0.9130	0.9167	0.75
0.2599	81.0	101	0.5905	0.9130	0.9167	0.75
0.2599	82.0	102	0.5893	0.9130	0.9167	0.75
0.2599	83.0	104	0.5872	0.9130	0.9167	0.75
0.2599	84.0	105	0.5855	0.9130	0.9167	0.75
0.2599	85.0	106	0.5852	0.9130	0.9167	0.75
0.2599	86.0	108	0.5835	0.9130	0.9167	0.75
0.2599	87.0	109	0.5835	0.9130	0.9167	0.75
0.2599	88.0	110	0.5831	0.9130	0.9167	0.75
0.2599	89.0	111	0.5822	0.9130	0.9167	0.75
0.2599	90.0	112	0.5815	0.9130	0.9167	0.75
0.2599	91.0	114	0.5803	0.9130	0.9167	0.75
0.2599	92.0	115	0.5779	0.9130	0.9167	0.75
0.2599	93.0	116	0.5770	0.9130	0.9167	0.75
0.2599	94.0	118	0.5758	0.9130	0.9167	0.75
0.2599	95.0	119	0.5748	0.9130	0.9167	0.75
0.2599	96.0	120	0.5744	0.9130	0.9167	0.75
0.2599	97.0	121	0.5739	0.9130	0.9167	0.75
0.2599	98.0	122	0.5730	0.9130	0.9167	0.75
0.2599	99.0	124	0.5710	0.9130	0.9167	0.75
0.2599	100.0	125	0.5703	0.9130	0.9167	0.75
0.2599	101.0	126	0.5687	0.9130	0.9167	0.75
0.2599	102.0	128	0.5664	0.9130	0.9167	0.75
0.2599	103.0	129	0.5657	0.9130	0.9167	0.75
0.2599	104.0	130	0.5657	0.9130	0.9167	0.75
0.2599	105.0	131	0.5639	0.9130	0.9167	0.75
0.2599	106.0	132	0.5642	0.9130	0.9167	0.75
0.2599	107.0	134	0.5617	0.9130	0.9167	0.75
0.2599	108.0	135	0.5604	0.9130	0.9167	0.75
0.2599	109.0	136	0.5598	0.9130	0.9167	0.75
0.2599	110.0	138	0.5579	0.9130	0.9167	0.75
0.2599	111.0	139	0.5566	0.8936	0.8958	0.75
0.2599	112.0	140	0.5561	0.9130	0.9167	0.75
0.2599	113.0	141	0.5567	0.8936	0.8958	0.75
0.2599	114.0	142	0.5571	0.8936	0.8958	0.75
0.2599	115.0	144	0.5536	0.8936	0.8958	0.75
0.2599	116.0	145	0.5537	0.8936	0.8958	0.75
0.2599	117.0	146	0.5510	0.8936	0.8958	0.75
0.2599	118.0	148	0.5496	0.8936	0.8958	0.75
0.2599	119.0	149	0.5492	0.9130	0.9167	0.75
0.2599	120.0	150	0.5492	0.9130	0.9167	0.75
0.2599	121.0	151	0.5490	0.9333	0.9375	0.75
0.2599	122.0	152	0.5483	0.9130	0.9167	0.75
0.2599	123.0	154	0.5464	0.9130	0.9167	0.75
0.2599	124.0	155	0.5477	0.9130	0.9167	0.75
0.2599	125.0	156	0.5469	0.9130	0.9167	0.75
0.2599	126.0	158	0.5445	0.9130	0.9167	0.75
0.2599	127.0	159	0.5450	0.9130	0.9167	0.75
0.2599	128.0	160	0.5436	0.9130	0.9167	0.75
0.2599	129.0	161	0.5433	0.9130	0.9167	0.75
0.2599	130.0	162	0.5417	0.9130	0.9167	0.75
0.2599	131.0	164	0.5416	0.9130	0.9167	0.75
0.2599	132.0	165	0.5403	0.9130	0.9167	0.75
0.2599	133.0	166	0.5404	0.9333	0.9375	0.75
0.2599	134.0	168	0.5390	0.9130	0.9167	0.75
0.2599	135.0	169	0.5389	0.9130	0.9167	0.75
0.2599	136.0	170	0.5376	0.9130	0.9167	0.75
0.2599	137.0	171	0.5374	0.9130	0.9167	0.75
0.2599	138.0	172	0.5372	0.9130	0.9167	0.75
0.2599	139.0	174	0.5348	0.9130	0.9167	0.75
0.2599	140.0	175	0.5356	0.9130	0.9167	0.75
0.2599	141.0	176	0.5355	0.9130	0.9167	0.75
0.2599	142.0	178	0.5323	0.9130	0.9167	0.75
0.2599	143.0	179	0.5323	0.9130	0.9167	0.75
0.2599	144.0	180	0.5332	0.9130	0.9167	0.75
0.2599	145.0	181	0.5320	0.9130	0.9167	0.75
0.2599	146.0	182	0.5315	0.9130	0.9167	0.75
0.2599	147.0	184	0.5301	0.9130	0.9167	0.75
0.2599	148.0	185	0.5284	0.9130	0.9167	0.75
0.2599	149.0	186	0.5296	0.9130	0.9167	0.75
0.2599	150.0	188	0.5301	0.9130	0.9167	0.75
0.2599	151.0	189	0.5282	0.9130	0.9167	0.75
0.2599	152.0	190	0.5263	0.9130	0.9167	0.75
0.2599	153.0	191	0.5263	0.9130	0.9167	0.75
0.2599	154.0	192	0.5270	0.9130	0.9167	0.75
0.2599	155.0	194	0.5274	0.9130	0.9167	0.75
0.2599	156.0	195	0.5264	0.9130	0.9167	0.75
0.2599	157.0	196	0.5281	0.9130	0.9167	0.75
0.2599	158.0	198	0.5232	0.9130	0.9167	0.75
0.2599	159.0	199	0.5218	0.9130	0.9167	0.75
0.2599	160.0	200	0.5212	0.9130	0.9167	0.75
0.2599	161.0	201	0.5214	0.9130	0.9167	0.75
0.2599	162.0	202	0.5222	0.9130	0.9167	0.75
0.2599	163.0	204	0.5210	0.9130	0.9167	0.75
0.2599	164.0	205	0.5207	0.9130	0.9167	0.75
0.2599	165.0	206	0.5210	0.9130	0.9167	0.75
0.2599	166.0	208	0.5195	0.9130	0.9167	0.75
0.2599	167.0	209	0.5217	0.9130	0.9167	0.75
0.2599	168.0	210	0.5207	0.9130	0.9167	0.75
0.2599	169.0	211	0.5190	0.9130	0.9167	0.75
0.2599	170.0	212	0.5181	0.9130	0.9167	0.75
0.2599	171.0	214	0.5183	0.9130	0.9167	0.75
0.2599	172.0	215	0.5183	0.9130	0.9167	0.75
0.2599	173.0	216	0.5202	0.9130	0.9167	0.75
0.2599	174.0	218	0.5180	0.9130	0.9167	0.75
0.2599	175.0	219	0.5189	0.9130	0.9167	0.75
0.2599	176.0	220	0.5157	0.9130	0.9167	0.75
0.2599	177.0	221	0.5168	0.9130	0.9167	0.75
0.2599	178.0	222	0.5161	0.9130	0.9167	0.75
0.2599	179.0	224	0.5160	0.9130	0.9167	0.75
0.2599	180.0	225	0.5178	0.9130	0.9167	0.75
0.2599	181.0	226	0.5166	0.9130	0.9167	0.75
0.2599	182.0	228	0.5146	0.9130	0.9167	0.75
0.2599	183.0	229	0.5143	0.9130	0.9167	0.75
0.2599	184.0	230	0.5128	0.9130	0.9167	0.75
0.2599	185.0	231	0.5111	0.9130	0.9167	0.75
0.2599	186.0	232	0.5119	0.9333	0.9375	0.75
0.2599	187.0	234	0.5116	0.9130	0.9167	0.75
0.2599	188.0	235	0.5099	0.9130	0.9167	0.75
0.2599	189.0	236	0.5108	0.9130	0.9167	0.75
0.2599	190.0	238	0.5102	0.9130	0.9167	0.75
0.2599	191.0	239	0.5103	0.9130	0.9167	0.75
0.2599	192.0	240	0.5102	0.9130	0.9167	0.75
0.2599	193.0	241	0.5102	0.9130	0.9167	0.75
0.2599	194.0	242	0.5110	0.9130	0.9167	0.75
0.2599	195.0	244	0.5093	0.9130	0.9167	0.75
0.2599	196.0	245	0.5102	0.9130	0.9167	0.75
0.2599	197.0	246	0.5094	0.9130	0.9167	0.75
0.2599	198.0	248	0.5082	0.9130	0.9167	0.75
0.2599	199.0	249	0.5069	0.9362	0.9375	0.8333
0.2599	200.0	250	0.5081	0.9130	0.9167	0.75
0.2599	201.0	251	0.5082	0.9130	0.9167	0.75
0.2599	202.0	252	0.5090	0.9130	0.9167	0.75
0.2599	203.0	254	0.5076	0.9130	0.9167	0.75
0.2599	204.0	255	0.5081	0.9130	0.9167	0.75
0.2599	205.0	256	0.5091	0.9130	0.9167	0.75
0.2599	206.0	258	0.5069	0.9130	0.9167	0.75
0.2599	207.0	259	0.5067	0.9130	0.9167	0.75
0.2599	208.0	260	0.5061	0.9362	0.9375	0.8333
0.2599	209.0	261	0.5076	0.9130	0.9167	0.75
0.2599	210.0	262	0.5082	0.9130	0.9167	0.75
0.2599	211.0	264	0.5069	0.9130	0.9167	0.75
0.2599	212.0	265	0.5074	0.9130	0.9167	0.75
0.2599	213.0	266	0.5077	0.9130	0.9167	0.75
0.2599	214.0	268	0.5058	0.9130	0.9167	0.75
0.2599	215.0	269	0.5063	0.9130	0.9167	0.75
0.2599	216.0	270	0.5059	0.9130	0.9167	0.75
0.2599	217.0	271	0.5059	0.9130	0.9167	0.75
0.2599	218.0	272	0.5050	0.9130	0.9167	0.75
0.2599	219.0	274	0.5056	0.9130	0.9167	0.75
0.2599	220.0	275	0.5053	0.9130	0.9167	0.75
0.2599	221.0	276	0.5058	0.9130	0.9167	0.75
0.2599	222.0	278	0.5051	0.9130	0.9167	0.75
0.2599	223.0	279	0.5047	0.9130	0.9167	0.75
0.2599	224.0	280	0.5041	0.9362	0.9375	0.8333
0.2599	225.0	281	0.5049	0.9130	0.9167	0.75
0.2599	226.0	282	0.5046	0.9362	0.9375	0.8333
0.2599	227.0	284	0.5078	0.9130	0.9167	0.75
0.2599	228.0	285	0.5064	0.9130	0.9167	0.75
0.2599	229.0	286	0.5065	0.9130	0.9167	0.75
0.2599	230.0	288	0.5066	0.9130	0.9167	0.75
0.2599	231.0	289	0.5058	0.9130	0.9167	0.75
0.2599	232.0	290	0.5067	0.9130	0.9167	0.75
0.2599	233.0	291	0.5079	0.9130	0.9167	0.75
0.2599	234.0	292	0.5085	0.9130	0.9167	0.75
0.2599	235.0	294	0.5073	0.9130	0.9167	0.75
0.2599	236.0	295	0.5023	0.9362	0.9375	0.8333
0.2599	237.0	296	0.5030	0.9362	0.9375	0.8333
0.2599	238.0	298	0.5044	0.9130	0.9167	0.75
0.2599	239.0	299	0.5055	0.9130	0.9167	0.75
0.2599	240.0	300	0.5062	0.9130	0.9167	0.75

Framework versions

• Transformers 4.35.0
• Pytorch 2.1.0+cu121
• Datasets 2.14.6
• Tokenizers 0.14.1