multiberts-seed_0_winobias_classifieronly

asun17904/multiberts-seed_0_winobias_classifieronly

multiberts-seed_0_winobias_classifieronly is a text classification model from asun17904. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

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

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Mar 24, 2023
Updated: Mar 24, 2023
SHA: 7429ca32

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Model card

From the Hugging Face model README

multiberts-seed_0_winobias_classifieronly

This model is a fine-tuned version of google/multiberts-seed_0 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6937
Accuracy: 0.5088
Tp: 0.3011
Tn: 0.2077
Fp: 0.2923
Fn: 0.1989

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: 5e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Tp	Tn	Fp	Fn
0.6992	0.8	20	0.6945	0.4943	0.2285	0.2658	0.2342	0.2715
0.7005	1.6	40	0.6944	0.4937	0.2702	0.2235	0.2765	0.2298
0.7025	2.4	60	0.6958	0.5032	0.4457	0.0574	0.4426	0.0543
0.6937	3.2	80	0.6943	0.5044	0.3403	0.1641	0.3359	0.1597
0.6935	4.0	100	0.6942	0.4943	0.2847	0.2096	0.2904	0.2153
0.6995	4.8	120	0.6942	0.4962	0.2702	0.2260	0.2740	0.2298
0.7035	5.6	140	0.6955	0.5	0.4324	0.0676	0.4324	0.0676
0.7001	6.4	160	0.6941	0.5	0.2437	0.2563	0.2437	0.2563
0.6967	7.2	180	0.6941	0.5032	0.2418	0.2614	0.2386	0.2582
0.6934	8.0	200	0.6943	0.4987	0.3472	0.1515	0.3485	0.1528
0.6963	8.8	220	0.6941	0.4956	0.3112	0.1843	0.3157	0.1888
0.6962	9.6	240	0.6940	0.5006	0.3112	0.1894	0.3106	0.1888
0.6955	10.4	260	0.6944	0.4949	0.3580	0.1370	0.3630	0.1420
0.7032	11.2	280	0.6941	0.4912	0.2683	0.2229	0.2771	0.2317
0.6996	12.0	300	0.6943	0.4949	0.3580	0.1370	0.3630	0.1420
0.6995	12.8	320	0.6940	0.5032	0.3188	0.1843	0.3157	0.1812
0.6985	13.6	340	0.6939	0.5057	0.2330	0.2727	0.2273	0.2670
0.696	14.4	360	0.6947	0.5038	0.4211	0.0827	0.4173	0.0789
0.6988	15.2	380	0.6941	0.4937	0.2854	0.2083	0.2917	0.2146
0.6998	16.0	400	0.6942	0.5044	0.2191	0.2854	0.2146	0.2809
0.6971	16.8	420	0.6940	0.5063	0.2323	0.2740	0.2260	0.2677
0.704	17.6	440	0.6939	0.4937	0.2664	0.2273	0.2727	0.2336
0.695	18.4	460	0.6940	0.4956	0.2797	0.2159	0.2841	0.2203
0.6992	19.2	480	0.6940	0.4949	0.2872	0.2077	0.2923	0.2128
0.6869	20.0	500	0.6940	0.4880	0.3150	0.1730	0.3270	0.1850
0.7022	20.8	520	0.6939	0.4968	0.3239	0.1730	0.3270	0.1761
0.6961	21.6	540	0.6942	0.5019	0.3857	0.1162	0.3838	0.1143
0.7024	22.4	560	0.6940	0.4962	0.3453	0.1509	0.3491	0.1547
0.6995	23.2	580	0.6940	0.5019	0.3542	0.1477	0.3523	0.1458
0.7	24.0	600	0.6939	0.5019	0.3131	0.1888	0.3112	0.1869
0.7035	24.8	620	0.6939	0.5	0.3396	0.1604	0.3396	0.1604
0.6978	25.6	640	0.6938	0.5133	0.2064	0.3068	0.1932	0.2936
0.7032	26.4	660	0.6938	0.4981	0.2399	0.2582	0.2418	0.2601
0.6898	27.2	680	0.6938	0.4956	0.2449	0.2506	0.2494	0.2551
0.6923	28.0	700	0.6939	0.4924	0.2929	0.1995	0.3005	0.2071
0.7025	28.8	720	0.6938	0.4968	0.2809	0.2159	0.2841	0.2191
0.6999	29.6	740	0.6943	0.5025	0.3838	0.1187	0.3813	0.1162
0.6993	30.4	760	0.6940	0.5006	0.3573	0.1433	0.3567	0.1427
0.7013	31.2	780	0.6939	0.4968	0.3333	0.1635	0.3365	0.1667
0.6985	32.0	800	0.6939	0.4981	0.3460	0.1521	0.3479	0.1540
0.6957	32.8	820	0.6938	0.5076	0.3277	0.1799	0.3201	0.1723
0.6978	33.6	840	0.6937	0.5107	0.2475	0.2633	0.2367	0.2525
0.6953	34.4	860	0.6938	0.5133	0.3201	0.1932	0.3068	0.1799
0.6923	35.2	880	0.6939	0.5	0.3485	0.1515	0.3485	0.1515
0.6947	36.0	900	0.6939	0.4987	0.3491	0.1496	0.3504	0.1509
0.7018	36.8	920	0.6937	0.5095	0.3018	0.2077	0.2923	0.1982
0.6957	37.6	940	0.6939	0.4975	0.3403	0.1572	0.3428	0.1597
0.698	38.4	960	0.6939	0.4981	0.3415	0.1566	0.3434	0.1585
0.6902	39.2	980	0.6938	0.4968	0.3289	0.1679	0.3321	0.1711
0.6973	40.0	1000	0.6938	0.4956	0.3346	0.1610	0.3390	0.1654
0.6962	40.8	1020	0.6938	0.5025	0.3194	0.1831	0.3169	0.1806
0.699	41.6	1040	0.6937	0.5019	0.3093	0.1926	0.3074	0.1907
0.6965	42.4	1060	0.6937	0.5013	0.2816	0.2197	0.2803	0.2184
0.694	43.2	1080	0.6937	0.5013	0.2677	0.2336	0.2664	0.2323
0.699	44.0	1100	0.6937	0.4962	0.2664	0.2298	0.2702	0.2336
0.6932	44.8	1120	0.6937	0.4975	0.2645	0.2330	0.2670	0.2355
0.6994	45.6	1140	0.6937	0.5006	0.2696	0.2311	0.2689	0.2304
0.7008	46.4	1160	0.6937	0.5095	0.2992	0.2102	0.2898	0.2008
0.7006	47.2	1180	0.6937	0.5082	0.3049	0.2033	0.2967	0.1951
0.6954	48.0	1200	0.6937	0.5101	0.3030	0.2071	0.2929	0.1970
0.7044	48.8	1220	0.6937	0.5088	0.3030	0.2058	0.2942	0.1970
0.6993	49.6	1240	0.6937	0.5088	0.3011	0.2077	0.2923	0.1989

Framework versions

Transformers 4.26.1
Pytorch 1.13.1
Datasets 2.10.1
Tokenizers 0.13.2

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Mar 24, 2023
Updated: Mar 24, 2023