PeptideGPT_non_fouling

aayush14/PeptideGPT_non_fouling

PeptideGPT_non_fouling is a machine learning model from aayush14. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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Hugging Face

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At a glance

License: apache-2.0
Model type: gpt2
Access: Public
Created: Sep 30, 2024
Updated: Sep 30, 2024
SHA: fdd54838

Base models

nferruz/ProtGPT2

Model card

From the Hugging Face model README

output_nf_3

This model is a fine-tuned version of nferruz/ProtGPT2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 5.6642
Accuracy: 0.3099

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-06
train_batch_size: 1
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 200.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
12.1762	1.0	9	11.8181	0.0029
11.6538	2.0	18	11.3468	0.0010
11.2876	3.0	27	10.9127	0.0010
10.8664	4.0	36	10.5162	0.0010
10.6184	5.0	45	10.1817	0.0020
10.3132	6.0	54	9.8765	0.0010
9.9087	7.0	63	9.6073	0.0010
9.6953	8.0	72	9.3244	0.0
9.3741	9.0	81	9.0318	0.0
9.2045	10.0	90	8.7461	0.0
8.9079	11.0	99	8.4755	0.0020
8.7047	12.0	108	8.2222	0.0117
8.4622	13.0	117	7.9951	0.0313
8.2649	14.0	126	7.8052	0.0655
8.043	15.0	135	7.6495	0.1065
7.9092	16.0	144	7.5160	0.1378
7.7103	17.0	153	7.3881	0.1691
7.5701	18.0	162	7.2693	0.1818
7.4483	19.0	171	7.1544	0.1994
7.314	20.0	180	7.0469	0.2160
7.2101	21.0	189	6.9440	0.2326
7.1026	22.0	198	6.8542	0.2366
6.9954	23.0	207	6.7684	0.2483
6.9206	24.0	216	6.6851	0.2512
6.8588	25.0	225	6.6217	0.2561
6.7975	26.0	234	6.5621	0.2590
6.7355	27.0	243	6.5111	0.2610
6.6928	28.0	252	6.4630	0.2639
6.6483	29.0	261	6.4137	0.2698
6.6169	30.0	270	6.3675	0.2717
6.5498	31.0	279	6.3292	0.2747
6.5385	32.0	288	6.2967	0.2766
6.5111	33.0	297	6.2592	0.2786
6.4748	34.0	306	6.2316	0.2815
6.4575	35.0	315	6.2096	0.2835
6.4251	36.0	324	6.1847	0.2845
6.4096	37.0	333	6.1613	0.2854
6.3741	38.0	342	6.1402	0.2854
6.3645	39.0	351	6.1285	0.2874
6.3511	40.0	360	6.1134	0.2874
6.3254	41.0	369	6.0957	0.2874
6.3077	42.0	378	6.0818	0.2874
6.301	43.0	387	6.0688	0.2874
6.2846	44.0	396	6.0511	0.2884
6.2739	45.0	405	6.0398	0.2893
6.2569	46.0	414	6.0301	0.2913
6.258	47.0	423	6.0176	0.2913
6.2273	48.0	432	6.0037	0.2933
6.2256	49.0	441	5.9962	0.2933
6.2065	50.0	450	5.9869	0.2933
6.1991	51.0	459	5.9756	0.2933
6.1895	52.0	468	5.9682	0.2942
6.1763	53.0	477	5.9611	0.2942
6.1734	54.0	486	5.9535	0.2942
6.1702	55.0	495	5.9457	0.2942
6.1556	56.0	504	5.9376	0.2952
6.1481	57.0	513	5.9306	0.2952
6.1425	58.0	522	5.9222	0.2942
6.1416	59.0	531	5.9170	0.2942
6.1328	60.0	540	5.9142	0.2942
6.1176	61.0	549	5.9064	0.2942
6.1091	62.0	558	5.9010	0.2942
6.104	63.0	567	5.8961	0.2942
6.0986	64.0	576	5.8915	0.2942
6.089	65.0	585	5.8854	0.2952
6.0734	66.0	594	5.8810	0.2942
6.0905	67.0	603	5.8762	0.2942
6.0701	68.0	612	5.8737	0.2962
6.0595	69.0	621	5.8694	0.2962
6.0616	70.0	630	5.8661	0.2962
6.0512	71.0	639	5.8635	0.2962
6.0415	72.0	648	5.8613	0.2962
6.0391	73.0	657	5.8583	0.2962
6.032	74.0	666	5.8548	0.2962
6.0317	75.0	675	5.8511	0.2962
6.0343	76.0	684	5.8479	0.2972
6.0156	77.0	693	5.8435	0.2981
6.0167	78.0	702	5.8403	0.2981
6.0052	79.0	711	5.8364	0.2981
6.0057	80.0	720	5.8336	0.2981
6.0001	81.0	729	5.8319	0.2981
6.001	82.0	738	5.8288	0.2991
5.9905	83.0	747	5.8266	0.3011
5.9906	84.0	756	5.8242	0.3021
5.9862	85.0	765	5.8216	0.3021
5.9829	86.0	774	5.8191	0.3050
5.9725	87.0	783	5.8173	0.3069
5.9795	88.0	792	5.8142	0.3089
5.9695	89.0	801	5.8115	0.3069
5.9607	90.0	810	5.8081	0.3089
5.9605	91.0	819	5.8057	0.3089
5.9591	92.0	828	5.8037	0.3079
5.9481	93.0	837	5.8011	0.3069
5.9501	94.0	846	5.7983	0.3079
5.948	95.0	855	5.7943	0.3089
5.9488	96.0	864	5.7907	0.3109
5.9449	97.0	873	5.7888	0.3118
5.9357	98.0	882	5.7872	0.3099
5.9363	99.0	891	5.7834	0.3079
5.9368	100.0	900	5.7817	0.3099
5.9215	101.0	909	5.7791	0.3099
5.9264	102.0	918	5.7749	0.3099
5.9126	103.0	927	5.7725	0.3089
5.9163	104.0	936	5.7698	0.3069
5.9183	105.0	945	5.7673	0.3069
5.9154	106.0	954	5.7639	0.3089
5.9149	107.0	963	5.7612	0.3079
5.9082	108.0	972	5.7579	0.3089
5.9051	109.0	981	5.7559	0.3079
5.908	110.0	990	5.7531	0.3079
5.901	111.0	999	5.7502	0.3079
5.9064	112.0	1008	5.7484	0.3089
5.895	113.0	1017	5.7460	0.3099
5.894	114.0	1026	5.7438	0.3089
5.8809	115.0	1035	5.7419	0.3079
5.8893	116.0	1044	5.7419	0.3079
5.8874	117.0	1053	5.7392	0.3069
5.8798	118.0	1062	5.7349	0.3089
5.8826	119.0	1071	5.7324	0.3099
5.8736	120.0	1080	5.7299	0.3099
5.8751	121.0	1089	5.7270	0.3099
5.8699	122.0	1098	5.7253	0.3099
5.8802	123.0	1107	5.7231	0.3099
5.8707	124.0	1116	5.7240	0.3099
5.8653	125.0	1125	5.7232	0.3109
5.8693	126.0	1134	5.7180	0.3109
5.8662	127.0	1143	5.7147	0.3109
5.8539	128.0	1152	5.7132	0.3099
5.8611	129.0	1161	5.7127	0.3099
5.8495	130.0	1170	5.7135	0.3079
5.8602	131.0	1179	5.7111	0.3089
5.8512	132.0	1188	5.7077	0.3109
5.8493	133.0	1197	5.7050	0.3109
5.8477	134.0	1206	5.7041	0.3099
5.8464	135.0	1215	5.7042	0.3089
5.8459	136.0	1224	5.7023	0.3099
5.8475	137.0	1233	5.7000	0.3099
5.8384	138.0	1242	5.6982	0.3099
5.8453	139.0	1251	5.6976	0.3089
5.8441	140.0	1260	5.6973	0.3089
5.838	141.0	1269	5.6971	0.3079
5.8463	142.0	1278	5.6950	0.3099
5.8385	143.0	1287	5.6921	0.3099
5.8354	144.0	1296	5.6909	0.3099
5.8283	145.0	1305	5.6908	0.3079
5.8363	146.0	1314	5.6902	0.3079
5.8433	147.0	1323	5.6890	0.3079
5.8302	148.0	1332	5.6890	0.3079
5.8276	149.0	1341	5.6881	0.3089
5.8366	150.0	1350	5.6864	0.3089
5.826	151.0	1359	5.6852	0.3099
5.8293	152.0	1368	5.6844	0.3099
5.8278	153.0	1377	5.6834	0.3099
5.8239	154.0	1386	5.6830	0.3089
5.8262	155.0	1395	5.6818	0.3089
5.8253	156.0	1404	5.6808	0.3099
5.8169	157.0	1413	5.6793	0.3109
5.8201	158.0	1422	5.6795	0.3109
5.8077	159.0	1431	5.6799	0.3099
5.8222	160.0	1440	5.6789	0.3099
5.8191	161.0	1449	5.6778	0.3099
5.83	162.0	1458	5.6768	0.3099
5.8183	163.0	1467	5.6757	0.3109
5.8124	164.0	1476	5.6747	0.3109
5.8119	165.0	1485	5.6745	0.3109
5.821	166.0	1494	5.6744	0.3099
5.807	167.0	1503	5.6737	0.3099
5.8177	168.0	1512	5.6725	0.3109
5.8046	169.0	1521	5.6710	0.3109
5.8093	170.0	1530	5.6708	0.3109
5.8145	171.0	1539	5.6710	0.3109
5.803	172.0	1548	5.6704	0.3109
5.8038	173.0	1557	5.6697	0.3109
5.807	174.0	1566	5.6689	0.3109
5.7974	175.0	1575	5.6683	0.3109
5.8089	176.0	1584	5.6688	0.3109
5.8067	177.0	1593	5.6693	0.3109
5.8092	178.0	1602	5.6695	0.3109
5.8047	179.0	1611	5.6687	0.3099
5.8007	180.0	1620	5.6679	0.3099
5.8041	181.0	1629	5.6672	0.3099
5.8072	182.0	1638	5.6667	0.3099
5.8093	183.0	1647	5.6662	0.3099
5.7948	184.0	1656	5.6658	0.3099
5.7968	185.0	1665	5.6656	0.3099
5.8033	186.0	1674	5.6653	0.3099
5.8031	187.0	1683	5.6651	0.3099
5.7953	188.0	1692	5.6650	0.3099
5.8085	189.0	1701	5.6647	0.3099
5.8021	190.0	1710	5.6646	0.3099
5.7995	191.0	1719	5.6643	0.3099
5.8057	192.0	1728	5.6642	0.3099
5.7989	193.0	1737	5.6642	0.3099
5.7977	194.0	1746	5.6642	0.3099
5.8009	195.0	1755	5.6644	0.3099
5.7988	196.0	1764	5.6645	0.3099
5.8016	197.0	1773	5.6645	0.3099
5.7929	198.0	1782	5.6645	0.3099
5.7973	199.0	1791	5.6645	0.3099
5.8022	200.0	1800	5.6645	0.3099

Framework versions

Transformers 4.38.0.dev0
Pytorch 2.2.0
Datasets 2.16.1
Tokenizers 0.15.1

Type: gpt2
License: apache-2.0
Created: Sep 30, 2024
Updated: Sep 30, 2024