MAE-CT-M1N0-v11

This model is a fine-tuned version of beingbatman/MAE-CT-M1N0-v11 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.9107
• Accuracy: 0.7407

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: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• training_steps: 6600

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0957	0.0102	67	1.0947	0.6176
0.2452	1.0102	134	1.1772	0.6765
0.5144	2.0102	201	1.5596	0.6471
0.1315	3.0102	268	1.4470	0.5588
0.0398	4.0102	335	1.5700	0.5882
0.1834	5.0102	402	1.2757	0.7059
0.1818	6.0102	469	1.5364	0.7059
0.0496	7.0102	536	1.6521	0.7353
0.0009	8.0102	603	1.8430	0.6765
0.141	9.0102	670	2.2428	0.6176
0.0338	10.0102	737	2.3844	0.6176
0.0353	11.0102	804	2.0932	0.7059
0.3218	12.0102	871	2.0158	0.6471
0.1485	13.0102	938	1.8430	0.6176
0.004	14.0102	1005	2.1836	0.5882
0.1743	15.0102	1072	2.1859	0.6471
0.0932	16.0102	1139	1.6879	0.7353
0.0039	17.0102	1206	2.0492	0.6471
0.2276	18.0102	1273	2.2761	0.5882
0.5771	19.0102	1340	2.5674	0.6471
0.1686	20.0102	1407	2.2761	0.6471
0.3135	21.0102	1474	2.2901	0.6176
0.0004	22.0102	1541	2.1465	0.7353
0.1221	23.0102	1608	2.2524	0.6471
0.0717	24.0102	1675	2.5812	0.5882
0.0763	25.0102	1742	2.9429	0.6176
0.0001	26.0102	1809	2.3691	0.7059
0.3076	27.0102	1876	2.7487	0.6176
0.2701	28.0102	1943	2.1523	0.6471
0.0018	29.0102	2010	2.9072	0.6176
0.096	30.0102	2077	2.9151	0.5882
0.2654	31.0102	2144	2.8686	0.6471
0.0002	32.0102	2211	2.6399	0.6471
0.0002	33.0102	2278	2.7440	0.6471
0.0113	34.0102	2345	2.5598	0.6471
0.0001	35.0102	2412	2.9623	0.5882
0.1484	36.0102	2479	2.5132	0.6765
0.0001	37.0102	2546	2.7195	0.6176
0.0004	38.0102	2613	1.9358	0.7647
0.0	39.0102	2680	2.6720	0.6471
0.0	40.0102	2747	2.9154	0.6176
0.0	41.0102	2814	2.9176	0.6176
0.0	42.0102	2881	2.9299	0.6176
0.0	43.0102	2948	2.8822	0.5882
0.0007	44.0102	3015	3.0881	0.6176
0.0001	45.0102	3082	3.3474	0.5882
0.0	46.0102	3149	3.2999	0.5882
0.0005	47.0102	3216	3.3930	0.5882
0.0001	48.0102	3283	3.4111	0.5882
0.0245	49.0102	3350	3.1914	0.6176
0.0003	50.0102	3417	3.0377	0.6765
0.0024	51.0102	3484	3.2830	0.5882
0.0001	52.0102	3551	2.5779	0.7059
0.0001	53.0102	3618	3.5160	0.5588
0.0	54.0102	3685	3.4892	0.5882
0.0	55.0102	3752	3.3148	0.5882
0.0	56.0102	3819	3.3751	0.5882
0.2024	57.0102	3886	3.4587	0.6176
0.0009	58.0102	3953	3.2979	0.5882
0.0	59.0102	4020	3.5841	0.5882
0.0001	60.0102	4087	3.4411	0.5882
0.0006	61.0102	4154	3.0952	0.6471
0.0	62.0102	4221	3.2242	0.5882
0.0947	63.0102	4288	3.1971	0.6176
0.0	64.0102	4355	3.3249	0.5882
0.0	65.0102	4422	3.5612	0.5882
0.0	66.0102	4489	3.6243	0.5882
0.0	67.0102	4556	3.3772	0.6176
0.0	68.0102	4623	3.4673	0.6176
0.0	69.0102	4690	3.4033	0.6176
0.0	70.0102	4757	3.2678	0.5882
0.0	71.0102	4824	3.2038	0.6471
0.135	72.0102	4891	2.8182	0.6176
0.0	73.0102	4958	3.1443	0.6765
0.0	74.0102	5025	3.7653	0.5882
0.0	75.0102	5092	3.7835	0.5882
0.0	76.0102	5159	3.7721	0.5882
0.0	77.0102	5226	3.7777	0.5882
0.0	78.0102	5293	3.7851	0.5882
0.0	79.0102	5360	3.7914	0.5882
0.0	80.0102	5427	3.7988	0.5882
0.0	81.0102	5494	3.8051	0.5882
0.0	82.0102	5561	3.8111	0.5882
0.0	83.0102	5628	3.8290	0.5882
0.0	84.0102	5695	3.8341	0.5882
0.0	85.0102	5762	3.8388	0.5882
0.0	86.0102	5829	3.8458	0.5882
0.0	87.0102	5896	3.8484	0.5882
0.0	88.0102	5963	3.8243	0.5882
0.0	89.0102	6030	3.8309	0.5882
0.0	90.0102	6097	3.8333	0.5882
0.0	91.0102	6164	3.8336	0.5882
0.0	92.0102	6231	3.8408	0.5882
0.0	93.0102	6298	3.8428	0.5882
0.0	94.0102	6365	3.8271	0.5882
0.0	95.0102	6432	3.8282	0.5882
0.0	96.0102	6499	3.8579	0.5882
0.0028	97.0102	6566	3.8781	0.5882
0.0	98.0052	6600	3.8801	0.5882

Framework versions

• Transformers 4.46.2
• Pytorch 2.0.1+cu117
• Datasets 3.0.1
• Tokenizers 0.20.0