sembr2023-bert-small

admko/sembr2023-bert-small

sembr2023-bert-small is a token classification model from admko. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.

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

Downloads · 30 days

3% of all-time downloads

All-time downloads

3.2K

Public

Parameters

28.5M

456 MB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin114 MB · 50%

At a glance

Task: Token Classification
Library: transformers
License: mit
Model type: bert
Access: Public
Created: Nov 27, 2023
Updated: Aug 3, 2025
SHA: 980e1776

Try a prompt

Base models

prajjwal1/bert-small

Model card

From the Hugging Face model README

sembr2023-bert-small

This model is a fine-tuned version of prajjwal1/bert-small on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2324
Precision: 0.7915
Recall: 0.8418
F1: 0.8159
Iou: 0.6890
Accuracy: 0.9651
Balanced Accuracy: 0.9097
Overall Accuracy: 0.9481

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: 128
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Iou	Accuracy	Balanced Accuracy	Overall Accuracy
0.4134	0.06	10	0.4107	0	0.0	0.0	0.0	0.9080	0.5	0.9080
0.371	0.12	20	0.3698	0	0.0	0.0	0.0	0.9080	0.5	0.9080
0.2913	0.18	30	0.2672	0.8443	0.4167	0.5580	0.3870	0.9393	0.7045	0.9283
0.2315	0.24	40	0.2184	0.8043	0.6761	0.7346	0.5806	0.9551	0.8297	0.9364
0.1693	0.3	50	0.2021	0.8064	0.7375	0.7704	0.6265	0.9596	0.8598	0.9396
0.1812	0.36	60	0.1869	0.8727	0.6847	0.7674	0.6225	0.9618	0.8373	0.9437
0.1745	0.42	70	0.1855	0.8021	0.7744	0.7880	0.6502	0.9617	0.8775	0.9421
0.1577	0.48	80	0.1817	0.8207	0.7641	0.7914	0.6548	0.9630	0.8736	0.9431
0.1458	0.55	90	0.1763	0.8183	0.7869	0.8023	0.6698	0.9643	0.8846	0.9449
0.1343	0.61	100	0.1772	0.8721	0.7372	0.7990	0.6652	0.9659	0.8631	0.9477
0.1442	0.67	110	0.1647	0.8388	0.7795	0.8081	0.6779	0.9659	0.8822	0.9483
0.1104	0.73	120	0.1678	0.8488	0.7679	0.8063	0.6755	0.9661	0.8770	0.9479
0.1089	0.79	130	0.1745	0.7882	0.8262	0.8068	0.6761	0.9636	0.9019	0.9434
0.1437	0.85	140	0.1768	0.7970	0.8206	0.8086	0.6787	0.9643	0.8997	0.9440
0.1104	0.91	150	0.1710	0.7961	0.8275	0.8115	0.6828	0.9646	0.9030	0.9446
0.0941	0.97	160	0.1647	0.8007	0.8167	0.8086	0.6787	0.9644	0.8980	0.9456
0.1146	1.03	170	0.1744	0.8026	0.8250	0.8136	0.6858	0.9652	0.9022	0.9456
0.0982	1.09	180	0.1636	0.8175	0.8191	0.8183	0.6925	0.9666	0.9003	0.9468
0.0875	1.15	190	0.1653	0.8305	0.8064	0.8183	0.6924	0.9671	0.8948	0.9476
0.0962	1.21	200	0.1610	0.8340	0.8076	0.8206	0.6958	0.9675	0.8957	0.9490
0.084	1.27	210	0.1671	0.8232	0.8177	0.8204	0.6955	0.9671	0.9000	0.9476
0.07	1.33	220	0.1665	0.7909	0.8545	0.8215	0.6971	0.9658	0.9158	0.9454
0.0785	1.39	230	0.1612	0.8411	0.8004	0.8202	0.6953	0.9677	0.8925	0.9496
0.0712	1.45	240	0.1638	0.8251	0.8161	0.8205	0.6957	0.9672	0.8993	0.9491
0.0683	1.52	250	0.1823	0.8097	0.8262	0.8179	0.6919	0.9662	0.9033	0.9463
0.0694	1.58	260	0.1717	0.8028	0.8408	0.8214	0.6969	0.9664	0.9099	0.9474
0.0809	1.64	270	0.1681	0.8304	0.8102	0.8202	0.6952	0.9673	0.8967	0.9491
0.0586	1.7	280	0.1811	0.8096	0.8391	0.8241	0.7008	0.9671	0.9096	0.9478
0.069	1.76	290	0.1855	0.8088	0.8284	0.8185	0.6928	0.9662	0.9043	0.9478
0.0739	1.82	300	0.1876	0.8148	0.8209	0.8178	0.6918	0.9664	0.9010	0.9476
0.0691	1.88	310	0.1741	0.8173	0.8206	0.8190	0.6934	0.9666	0.9010	0.9485
0.0728	1.94	320	0.1765	0.7941	0.8346	0.8139	0.6861	0.9649	0.9064	0.9469
0.0585	2.0	330	0.1800	0.8118	0.8166	0.8142	0.6866	0.9657	0.8987	0.9483
0.0602	2.06	340	0.1930	0.7969	0.8366	0.8162	0.6895	0.9654	0.9075	0.9461
0.0557	2.12	350	0.1832	0.7915	0.8401	0.8151	0.6879	0.9649	0.9089	0.9472
0.0491	2.18	360	0.1914	0.8131	0.8136	0.8134	0.6854	0.9657	0.8973	0.9489
0.0413	2.24	370	0.2116	0.7989	0.8288	0.8136	0.6857	0.9651	0.9038	0.9463
0.051	2.3	380	0.2073	0.7864	0.8454	0.8148	0.6875	0.9647	0.9111	0.9460
0.0529	2.36	390	0.1923	0.8103	0.8278	0.8190	0.6934	0.9663	0.9041	0.9496
0.0469	2.42	400	0.1808	0.8131	0.8217	0.8173	0.6911	0.9662	0.9013	0.9497
0.0579	2.48	410	0.2053	0.7795	0.8493	0.8129	0.6848	0.9640	0.9125	0.9464
0.0494	2.55	420	0.1953	0.7872	0.8457	0.8154	0.6883	0.9648	0.9113	0.9471
0.0468	2.61	430	0.1972	0.8064	0.8182	0.8123	0.6839	0.9652	0.8992	0.9488
0.0545	2.67	440	0.2116	0.7774	0.8455	0.8100	0.6807	0.9635	0.9105	0.9458
0.0544	2.73	450	0.1954	0.7868	0.8455	0.8151	0.6879	0.9647	0.9111	0.9472
0.044	2.79	460	0.2046	0.8149	0.8203	0.8175	0.6914	0.9663	0.9007	0.9491
0.0468	2.85	470	0.2036	0.8031	0.8321	0.8174	0.6911	0.9658	0.9057	0.9483
0.0457	2.91	480	0.1998	0.7923	0.8377	0.8144	0.6869	0.9649	0.9077	0.9479
0.0435	2.97	490	0.2077	0.7864	0.8432	0.8138	0.6860	0.9645	0.9100	0.9475
0.0489	3.03	500	0.2067	0.7933	0.8339	0.8131	0.6850	0.9647	0.9059	0.9478
0.0472	3.09	510	0.2204	0.7883	0.8464	0.8163	0.6896	0.9650	0.9117	0.9475
0.0469	3.15	520	0.2209	0.7821	0.8470	0.8132	0.6853	0.9642	0.9115	0.9467
0.0384	3.21	530	0.2147	0.7923	0.8367	0.8139	0.6862	0.9648	0.9072	0.9479
0.0322	3.27	540	0.2215	0.7842	0.8489	0.8153	0.6881	0.9646	0.9126	0.9475
0.0429	3.33	550	0.2184	0.7743	0.8504	0.8106	0.6815	0.9634	0.9127	0.9463
0.0348	3.39	560	0.2293	0.7642	0.8594	0.8090	0.6792	0.9627	0.9163	0.9451
0.0365	3.45	570	0.2221	0.7922	0.8411	0.8159	0.6891	0.9651	0.9094	0.9477
0.0374	3.52	580	0.2175	0.7917	0.8382	0.8143	0.6868	0.9648	0.9079	0.9479
0.0413	3.58	590	0.2111	0.8122	0.8243	0.8182	0.6924	0.9663	0.9025	0.9499
0.0362	3.64	600	0.2183	0.7883	0.8404	0.8135	0.6856	0.9646	0.9088	0.9479
0.0352	3.7	610	0.2124	0.8005	0.8340	0.8169	0.6905	0.9656	0.9065	0.9487
0.0301	3.76	620	0.2145	0.7993	0.8369	0.8177	0.6916	0.9657	0.9078	0.9488
0.0399	3.82	630	0.2188	0.8018	0.8318	0.8166	0.6900	0.9656	0.9055	0.9485
0.0366	3.88	640	0.2211	0.7969	0.8346	0.8153	0.6882	0.9652	0.9066	0.9478
0.0289	3.94	650	0.2201	0.7850	0.8468	0.8147	0.6874	0.9646	0.9116	0.9475
0.0367	4.0	660	0.2280	0.7859	0.8437	0.8138	0.6860	0.9645	0.9102	0.9475
0.0362	4.06	670	0.2226	0.7785	0.8502	0.8128	0.6846	0.9640	0.9128	0.9469
0.0376	4.12	680	0.2213	0.8006	0.8317	0.8159	0.6890	0.9655	0.9054	0.9490
0.0294	4.18	690	0.2212	0.8052	0.8271	0.8160	0.6892	0.9657	0.9034	0.9492
0.0318	4.24	700	0.2254	0.7874	0.8420	0.8138	0.6860	0.9646	0.9095	0.9477
0.0359	4.3	710	0.2250	0.7899	0.8432	0.8157	0.6887	0.9649	0.9102	0.9479
0.034	4.36	720	0.2264	0.7985	0.8380	0.8178	0.6917	0.9656	0.9083	0.9489
0.0334	4.42	730	0.2308	0.7871	0.8436	0.8144	0.6869	0.9646	0.9102	0.9475
0.036	4.48	740	0.2250	0.7936	0.8404	0.8163	0.6896	0.9652	0.9091	0.9485
0.0257	4.55	750	0.2267	0.7861	0.8456	0.8148	0.6874	0.9646	0.9112	0.9479
0.0354	4.61	760	0.2288	0.7943	0.8401	0.8166	0.6900	0.9653	0.9090	0.9484
0.0373	4.67	770	0.2320	0.7828	0.8471	0.8137	0.6859	0.9643	0.9117	0.9470
0.0272	4.73	780	0.2250	0.7994	0.8354	0.8170	0.6906	0.9656	0.9071	0.9487
0.034	4.79	790	0.2339	0.7861	0.8450	0.8145	0.6870	0.9646	0.9108	0.9473
0.0294	4.85	800	0.2262	0.7972	0.8381	0.8171	0.6908	0.9655	0.9082	0.9486
0.0353	4.91	810	0.2337	0.7833	0.8473	0.8140	0.6864	0.9644	0.9118	0.9472
0.0337	4.97	820	0.2273	0.7973	0.8372	0.8168	0.6903	0.9655	0.9078	0.9485
0.0309	5.03	830	0.2318	0.7917	0.8413	0.8157	0.6888	0.9650	0.9094	0.9481
0.026	5.09	840	0.2327	0.7932	0.8418	0.8168	0.6903	0.9653	0.9098	0.9483
0.0271	5.15	850	0.2317	0.7887	0.8459	0.8163	0.6896	0.9650	0.9115	0.9479
0.0352	5.21	860	0.2344	0.7914	0.8427	0.8162	0.6895	0.9651	0.9101	0.9481
0.0268	5.27	870	0.2306	0.7931	0.8417	0.8166	0.6901	0.9652	0.9097	0.9484
0.0248	5.33	880	0.2309	0.7889	0.8438	0.8155	0.6884	0.9649	0.9105	0.9480
0.0331	5.39	890	0.2306	0.7895	0.8432	0.8154	0.6884	0.9649	0.9102	0.9480
0.0265	5.45	900	0.2322	0.7944	0.8401	0.8166	0.6901	0.9653	0.9091	0.9484
0.0352	5.52	910	0.2326	0.7922	0.8419	0.8163	0.6896	0.9651	0.9098	0.9482
0.0368	5.58	920	0.2313	0.7911	0.8424	0.8160	0.6891	0.9651	0.9099	0.9481
0.0315	5.64	930	0.2313	0.7917	0.8420	0.8161	0.6893	0.9651	0.9098	0.9482
0.0251	5.7	940	0.2324	0.7919	0.8409	0.8156	0.6887	0.9650	0.9093	0.9481
0.0331	5.76	950	0.2327	0.7913	0.8414	0.8156	0.6886	0.9650	0.9095	0.9481
0.0361	5.82	960	0.2327	0.7904	0.8423	0.8155	0.6885	0.9650	0.9098	0.9480
0.0362	5.88	970	0.2325	0.7909	0.8419	0.8156	0.6887	0.9650	0.9097	0.9481
0.031	5.94	980	0.2324	0.7914	0.8418	0.8158	0.6889	0.9650	0.9097	0.9481
0.0316	6.0	990	0.2324	0.7915	0.8418	0.8159	0.6890	0.9651	0.9097	0.9481
0.0232	6.06	1000	0.2324	0.7915	0.8418	0.8159	0.6890	0.9651	0.9097	0.9481

Framework versions

Transformers 4.34.1
Pytorch 2.0.1
Datasets 2.14.6
Tokenizers 0.14.1

Task: Token Classification
Library: transformers
Type: bert
License: mit
Created: Nov 27, 2023
Updated: Aug 3, 2025