gpt2_winobias_finetuned

henryscheible/gpt2_winobias_finetuned

gpt2_winobias_finetuned is a text classification model from henryscheible. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.

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

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At a glance

Task: Text Classification
Library: transformers
License: mit
Model type: gpt2
Access: Public
Created: Mar 6, 2023
Updated: Mar 16, 2023
SHA: 4249fce3

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Model card

From the Hugging Face model README

gpt2_winobias_finetuned

This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.4430
Accuracy: 0.7153
Tp: 0.3725
Tn: 0.3428
Fp: 0.1572
Fn: 0.1275

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: 0.0001
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
0.7128	0.8	20	0.7014	0.5	0.0	0.5	0.0	0.5
0.7384	1.6	40	0.7479	0.5	0.0	0.5	0.0	0.5
0.7142	2.4	60	0.7035	0.5	0.0	0.5	0.0	0.5
0.7004	3.2	80	0.7548	0.5	0.5	0.0	0.5	0.0
0.7353	4.0	100	0.7191	0.5	0.0	0.5	0.0	0.5
0.7041	4.8	120	0.7120	0.5	0.5	0.0	0.5	0.0
0.7012	5.6	140	0.7019	0.5	0.0	0.5	0.0	0.5
0.695	6.4	160	0.7264	0.5	0.0	0.5	0.0	0.5
0.7069	7.2	180	0.6932	0.5	0.5	0.0	0.5	0.0
0.7208	8.0	200	0.7370	0.5	0.5	0.0	0.5	0.0
0.7203	8.8	220	0.6935	0.5	0.0	0.5	0.0	0.5
0.6968	9.6	240	0.6944	0.5	0.5	0.0	0.5	0.0
0.7162	10.4	260	0.7056	0.5	0.5	0.0	0.5	0.0
0.6966	11.2	280	0.6942	0.5	0.0	0.5	0.0	0.5
0.705	12.0	300	0.6963	0.5	0.0	0.5	0.0	0.5
0.7007	12.8	320	0.7010	0.4956	0.4716	0.0240	0.4760	0.0284
0.7039	13.6	340	0.6973	0.4937	0.4697	0.0240	0.4760	0.0303
0.6864	14.4	360	0.7336	0.4937	0.3946	0.0991	0.4009	0.1054
0.7068	15.2	380	0.7135	0.4987	0.1073	0.3914	0.1086	0.3927
0.6626	16.0	400	0.7278	0.5019	0.0259	0.4760	0.0240	0.4741
0.6502	16.8	420	0.7612	0.5025	0.2879	0.2146	0.2854	0.2121
0.5627	17.6	440	0.7975	0.5404	0.1932	0.3472	0.1528	0.3068
0.5473	18.4	460	0.7218	0.5972	0.3005	0.2967	0.2033	0.1995
0.4772	19.2	480	0.7505	0.6490	0.3529	0.2961	0.2039	0.1471
0.388	20.0	500	0.7515	0.6812	0.3624	0.3188	0.1812	0.1376
0.3102	20.8	520	0.9149	0.6894	0.3819	0.3074	0.1926	0.1181
0.2433	21.6	540	0.7770	0.7020	0.3630	0.3390	0.1610	0.1370
0.2379	22.4	560	0.9499	0.7102	0.3422	0.3681	0.1319	0.1578
0.1669	23.2	580	0.9379	0.7077	0.3794	0.3283	0.1717	0.1206
0.1622	24.0	600	0.9364	0.7077	0.3902	0.3176	0.1824	0.1098
0.1455	24.8	620	1.1195	0.6970	0.3359	0.3611	0.1389	0.1641
0.114	25.6	640	1.1392	0.7102	0.3580	0.3523	0.1477	0.1420
0.0714	26.4	660	1.4233	0.7165	0.3447	0.3718	0.1282	0.1553
0.0739	27.2	680	1.5302	0.7159	0.3567	0.3592	0.1408	0.1433
0.0774	28.0	700	2.3741	0.7096	0.3636	0.3460	0.1540	0.1364
0.0672	28.8	720	1.3433	0.7096	0.3567	0.3529	0.1471	0.1433
0.0616	29.6	740	1.6716	0.7172	0.3718	0.3453	0.1547	0.1282
0.0432	30.4	760	1.2928	0.7109	0.3561	0.3548	0.1452	0.1439
0.0417	31.2	780	1.6960	0.7052	0.3447	0.3605	0.1395	0.1553
0.0538	32.0	800	1.8484	0.7102	0.3516	0.3586	0.1414	0.1484
0.0513	32.8	820	2.0704	0.6963	0.3485	0.3479	0.1521	0.1515
0.0428	33.6	840	1.8172	0.7090	0.3630	0.3460	0.1540	0.1370
0.0317	34.4	860	1.8815	0.7121	0.3674	0.3447	0.1553	0.1326
0.0375	35.2	880	1.7032	0.7121	0.3561	0.3561	0.1439	0.1439
0.032	36.0	900	2.1972	0.7128	0.3573	0.3554	0.1446	0.1427
0.0173	36.8	920	2.2502	0.7165	0.3662	0.3504	0.1496	0.1338
0.0117	37.6	940	2.1330	0.7184	0.3687	0.3497	0.1503	0.1313
0.0206	38.4	960	2.0618	0.7191	0.3725	0.3466	0.1534	0.1275
0.0146	39.2	980	1.9688	0.7172	0.3592	0.3580	0.1420	0.1408
0.0108	40.0	1000	2.0846	0.7153	0.3592	0.3561	0.1439	0.1408
0.0131	40.8	1020	2.3518	0.7140	0.3592	0.3548	0.1452	0.1408
0.0095	41.6	1040	2.5874	0.7197	0.3712	0.3485	0.1515	0.1288
0.0331	42.4	1060	2.5151	0.7159	0.3649	0.3510	0.1490	0.1351
0.0037	43.2	1080	2.3016	0.7153	0.3643	0.3510	0.1490	0.1357
0.0212	44.0	1100	2.1693	0.7121	0.3554	0.3567	0.1433	0.1446
0.0109	44.8	1120	2.1769	0.7134	0.3580	0.3554	0.1446	0.1420
0.0032	45.6	1140	2.2651	0.7146	0.3649	0.3497	0.1503	0.1351
0.0122	46.4	1160	2.3623	0.7172	0.3712	0.3460	0.1540	0.1288
0.0029	47.2	1180	2.4197	0.7197	0.3763	0.3434	0.1566	0.1237
0.0197	48.0	1200	2.4860	0.7159	0.3718	0.3441	0.1559	0.1282
0.0127	48.8	1220	2.4478	0.7146	0.3725	0.3422	0.1578	0.1275
0.0273	49.6	1240	2.4430	0.7153	0.3725	0.3428	0.1572	0.1275

Framework versions

Transformers 4.26.1
Pytorch 1.13.1
Datasets 2.10.1
Tokenizers 0.13.2

Task: Text Classification
Library: transformers
Type: gpt2
License: mit
Created: Mar 6, 2023
Updated: Mar 16, 2023