mdeberta_all_15

ricardo-filho/mdeberta_all_15

mdeberta_all_15 is a token classification model from ricardo-filho. 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. --

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At a glance

Task: Token Classification
Library: transformers
License: mit
Model type: deberta-v2
Access: Public
Created: Dec 1, 2022
Updated: Dec 3, 2022
SHA: d9dc71bd

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Model card

From the Hugging Face model README

mdeberta_all

This model is a fine-tuned version of microsoft/mdeberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2148
Aerospacemanufacturer Precision: 0.7073
Aerospacemanufacturer Recall: 0.8406
Aerospacemanufacturer F1: 0.7682
Aerospacemanufacturer Number: 138
Anatomicalstructure Precision: 0.6762
Anatomicalstructure Recall: 0.7269
Anatomicalstructure F1: 0.7006
Anatomicalstructure Number: 227
Artwork Precision: 0.5802
Artwork Recall: 0.5802
Artwork F1: 0.5802
Artwork Number: 131
Artist Precision: 0.7565
Artist Recall: 0.7938
Artist F1: 0.7747
Artist Number: 1722
Athlete Precision: 0.7195
Athlete Recall: 0.7636
Athlete F1: 0.7409
Athlete Number: 719
Carmanufacturer Precision: 0.6806
Carmanufacturer Recall: 0.8176
Carmanufacturer F1: 0.7429
Carmanufacturer Number: 159
Cleric Precision: 0.6867
Cleric Recall: 0.5124
Cleric F1: 0.5869
Cleric Number: 201
Clothing Precision: 0.5797
Clothing Recall: 0.625
Clothing F1: 0.6015
Clothing Number: 128
Disease Precision: 0.6262
Disease Recall: 0.6768
Disease F1: 0.6505
Disease Number: 198
Drink Precision: 0.7296
Drink Recall: 0.8112
Drink F1: 0.7682
Drink Number: 143
Facility Precision: 0.6439
Facility Recall: 0.7203
Facility F1: 0.6800
Facility Number: 497
Food Precision: 0.6786
Food Recall: 0.5327
Food F1: 0.5969
Food Number: 214
Humansettlement Precision: 0.8594
Humansettlement Recall: 0.8792
Humansettlement F1: 0.8692
Humansettlement Number: 1689
Medicalprocedure Precision: 0.6545
Medicalprocedure Recall: 0.7606
Medicalprocedure F1: 0.7036
Medicalprocedure Number: 142
Medication/vaccine Precision: 0.7183
Medication/vaccine Recall: 0.765
Medication/vaccine F1: 0.7409
Medication/vaccine Number: 200
Musicalgrp Precision: 0.7132
Musicalgrp Recall: 0.7688
Musicalgrp F1: 0.7400
Musicalgrp Number: 372
Musicalwork Precision: 0.7513
Musicalwork Recall: 0.7052
Musicalwork F1: 0.7275
Musicalwork Number: 407
Org Precision: 0.6335
Org Recall: 0.6117
Org F1: 0.6224
Org Number: 667
Otherloc Precision: 0.7514
Otherloc Recall: 0.6205
Otherloc F1: 0.6797
Otherloc Number: 224
Otherper Precision: 0.4558
Otherper Recall: 0.5821
Otherper F1: 0.5112
Otherper Number: 859
Otherprod Precision: 0.6076
Otherprod Recall: 0.5543
Otherprod F1: 0.5797
Otherprod Number: 433
Politician Precision: 0.6228
Politician Recall: 0.4793
Politician F1: 0.5417
Politician Number: 603
Privatecorp Precision: 0.7159
Privatecorp Recall: 0.4884
Privatecorp F1: 0.5806
Privatecorp Number: 129
Publiccorp Precision: 0.56
Publiccorp Recall: 0.6914
Publiccorp F1: 0.6188
Publiccorp Number: 243
Scientist Precision: 0.4545
Scientist Recall: 0.4497
Scientist F1: 0.4521
Scientist Number: 189
Software Precision: 0.7159
Software Recall: 0.8046
Software F1: 0.7577
Software Number: 307
Sportsgrp Precision: 0.7845
Sportsgrp Recall: 0.8701
Sportsgrp F1: 0.8251
Sportsgrp Number: 385
Sportsmanager Precision: 0.6667
Sportsmanager Recall: 0.5361
Sportsmanager F1: 0.5943
Sportsmanager Number: 194
Station Precision: 0.7406
Station Recall: 0.8093
Station F1: 0.7734
Station Number: 194
Symptom Precision: 0.6316
Symptom Recall: 0.5581
Symptom F1: 0.5926
Symptom Number: 129
Vehicle Precision: 0.5514
Vehicle Recall: 0.6505
Vehicle F1: 0.5969
Vehicle Number: 206
Visualwork Precision: 0.7538
Visualwork Recall: 0.7951
Visualwork F1: 0.7739
Visualwork Number: 693
Writtenwork Precision: 0.6913
Writtenwork Recall: 0.6803
Writtenwork F1: 0.6858
Writtenwork Number: 563
Overall Precision: 0.6928
Overall Recall: 0.7142
Overall F1: 0.7033
Overall Accuracy: 0.9355

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15.0

Training results

Training Loss	Epoch	Step	Validation Loss	Aerospacemanufacturer Precision	Aerospacemanufacturer Recall	Aerospacemanufacturer F1	Aerospacemanufacturer Number	Anatomicalstructure Precision	Anatomicalstructure Recall	Anatomicalstructure F1	Anatomicalstructure Number	Artwork Precision	Artwork Recall	Artwork F1	Artwork Number	Artist Precision	Artist Recall	Artist F1	Artist Number	Athlete Precision	Athlete Recall	Athlete F1	Athlete Number	Carmanufacturer Precision	Carmanufacturer Recall	Carmanufacturer F1	Carmanufacturer Number	Cleric Precision	Cleric Recall	Cleric F1	Cleric Number	Clothing Precision	Clothing Recall	Clothing F1	Clothing Number	Disease Precision	Disease Recall	Disease F1	Disease Number	Drink Precision	Drink Recall	Drink F1	Drink Number	Facility Precision	Facility Recall	Facility F1	Facility Number	Food Precision	Food Recall	Food F1	Food Number	Humansettlement Precision	Humansettlement Recall	Humansettlement F1	Humansettlement Number	Medicalprocedure Precision	Medicalprocedure Recall	Medicalprocedure F1	Medicalprocedure Number	Medication/vaccine Precision	Medication/vaccine Recall	Medication/vaccine F1	Medication/vaccine Number	Musicalgrp Precision	Musicalgrp Recall	Musicalgrp F1	Musicalgrp Number	Musicalwork Precision	Musicalwork Recall	Musicalwork F1	Musicalwork Number	Org Precision	Org Recall	Org F1	Org Number	Otherloc Precision	Otherloc Recall	Otherloc F1	Otherloc Number	Otherper Precision	Otherper Recall	Otherper F1	Otherper Number	Otherprod Precision	Otherprod Recall	Otherprod F1	Otherprod Number	Politician Precision	Politician Recall	Politician F1	Politician Number	Privatecorp Precision	Privatecorp Recall	Privatecorp F1	Privatecorp Number	Publiccorp Precision	Publiccorp Recall	Publiccorp F1	Publiccorp Number	Scientist Precision	Scientist Recall	Scientist F1	Scientist Number	Software Precision	Software Recall	Software F1	Software Number	Sportsgrp Precision	Sportsgrp Recall	Sportsgrp F1	Sportsgrp Number	Sportsmanager Precision	Sportsmanager Recall	Sportsmanager F1	Sportsmanager Number	Station Precision	Station Recall	Station F1	Station Number	Symptom Precision	Symptom Recall	Symptom F1	Symptom Number	Vehicle Precision	Vehicle Recall	Vehicle F1	Vehicle Number	Visualwork Precision	Visualwork Recall	Visualwork F1	Visualwork Number	Writtenwork Precision	Writtenwork Recall	Writtenwork F1	Writtenwork Number	Overall Precision	Overall Recall	Overall F1	Overall Accuracy
0.2881	1.0	21353	0.2534	0.5191	0.6884	0.5919	138	0.5693	0.6872	0.6228	227	0.4366	0.4733	0.4542	131	0.7109	0.8055	0.7552	1722	0.6782	0.6801	0.6792	719	0.6552	0.7170	0.6847	159	0.4874	0.4826	0.485	201	0.4639	0.6016	0.5238	128	0.4799	0.7222	0.5766	198	0.55	0.6923	0.6130	143	0.5305	0.6640	0.5898	497	0.4042	0.7196	0.5176	214	0.8164	0.8792	0.8466	1689	0.5799	0.6901	0.6302	142	0.5945	0.755	0.6652	200	0.7445	0.6425	0.6898	372	0.6667	0.6634	0.6650	407	0.5585	0.5652	0.5618	667	0.6724	0.5223	0.5879	224	0.3835	0.4773	0.4253	859	0.5237	0.4596	0.4895	433	0.5176	0.4643	0.4895	603	0.4688	0.1163	0.1863	129	0.4207	0.6008	0.4949	243	0.4099	0.3492	0.3771	189	0.6686	0.7362	0.7008	307	0.7688	0.7948	0.7816	385	0.5136	0.5825	0.5459	194	0.6667	0.8041	0.7290	194	0.5588	0.1473	0.2331	129	0.4910	0.5291	0.5093	206	0.6662	0.7489	0.7052	693	0.6180	0.5861	0.6016	563	0.6136	0.6640	0.6378	0.9220
0.2195	2.0	42706	0.2288	0.6409	0.8406	0.7273	138	0.6908	0.6300	0.6590	227	0.5625	0.5496	0.5560	131	0.7336	0.8124	0.7710	1722	0.6466	0.8067	0.7178	719	0.6095	0.8050	0.6938	159	0.5848	0.4975	0.5376	201	0.5260	0.6328	0.5745	128	0.5427	0.6414	0.5880	198	0.7042	0.6993	0.7018	143	0.6157	0.7123	0.6604	497	0.6140	0.4907	0.5455	214	0.8454	0.8745	0.8597	1689	0.6125	0.6901	0.6490	142	0.6898	0.745	0.7163	200	0.7299	0.7339	0.7319	372	0.6901	0.7224	0.7059	407	0.6224	0.5907	0.6062	667	0.7312	0.6071	0.6634	224	0.4851	0.4750	0.4800	859	0.5994	0.4804	0.5333	433	0.5675	0.5091	0.5367	603	0.6905	0.4496	0.5446	129	0.5516	0.6379	0.5916	243	0.4570	0.3651	0.4059	189	0.7508	0.7459	0.7484	307	0.7833	0.8260	0.8040	385	0.7071	0.5103	0.5928	194	0.6920	0.7990	0.7416	194	0.4590	0.4341	0.4462	129	0.4717	0.7282	0.5725	206	0.7275	0.7821	0.7538	693	0.6618	0.6430	0.6523	563	0.6711	0.6946	0.6827	0.9317
0.1965	3.0	64059	0.2148	0.7073	0.8406	0.7682	138	0.6762	0.7269	0.7006	227	0.5802	0.5802	0.5802	131	0.7565	0.7938	0.7747	1722	0.7195	0.7636	0.7409	719	0.6806	0.8176	0.7429	159	0.6867	0.5124	0.5869	201	0.5797	0.625	0.6015	128	0.6262	0.6768	0.6505	198	0.7296	0.8112	0.7682	143	0.6439	0.7203	0.6800	497	0.6786	0.5327	0.5969	214	0.8594	0.8792	0.8692	1689	0.6545	0.7606	0.7036	142	0.7183	0.765	0.7409	200	0.7132	0.7688	0.7400	372	0.7513	0.7052	0.7275	407	0.6335	0.6117	0.6224	667	0.7514	0.6205	0.6797	224	0.4558	0.5821	0.5112	859	0.6076	0.5543	0.5797	433	0.6228	0.4793	0.5417	603	0.7159	0.4884	0.5806	129	0.56	0.6914	0.6188	243	0.4545	0.4497	0.4521	189	0.7159	0.8046	0.7577	307	0.7845	0.8701	0.8251	385	0.6667	0.5361	0.5943	194	0.7406	0.8093	0.7734	194	0.6316	0.5581	0.5926	129	0.5514	0.6505	0.5969	206	0.7538	0.7951	0.7739	693	0.6913	0.6803	0.6858	563	0.6928	0.7142	0.7033	0.9355
0.1665	4.0	85412	0.2193	0.7917	0.8261	0.8085	138	0.7069	0.7225	0.7146	227	0.5867	0.6718	0.6263	131	0.7710	0.7938	0.7823	1722	0.6962	0.7650	0.7290	719	0.7904	0.8302	0.8098	159	0.6221	0.5323	0.5737	201	0.5743	0.6641	0.6159	128	0.5966	0.7172	0.6514	198	0.7914	0.7692	0.7801	143	0.6395	0.7103	0.6730	497	0.6422	0.6121	0.6268	214	0.8338	0.9059	0.8683	1689	0.6711	0.7183	0.6939	142	0.7635	0.775	0.7692	200	0.7669	0.7608	0.7638	372	0.6872	0.7936	0.7366	407	0.7100	0.5982	0.6493	667	0.7181	0.7277	0.7228	224	0.4765	0.5553	0.5129	859	0.6225	0.5866	0.6040	433	0.6078	0.5191	0.5599	603	0.7222	0.5039	0.5936	129	0.6065	0.7737	0.6799	243	0.4783	0.5238	0.5	189	0.7313	0.7980	0.7632	307	0.8401	0.8597	0.8498	385	0.6058	0.6495	0.6269	194	0.7512	0.7938	0.7719	194	0.6983	0.6279	0.6612	129	0.5804	0.7184	0.6421	206	0.7571	0.8052	0.7804	693	0.6916	0.6892	0.6904	563	0.7012	0.7309	0.7158	0.9375
0.1314	5.0	106765	0.2272	0.7707	0.8768	0.8203	138	0.7137	0.7577	0.7350	227	0.6058	0.6336	0.6194	131	0.7229	0.8513	0.7819	1722	0.7361	0.7761	0.7556	719	0.6839	0.8302	0.7500	159	0.5845	0.6020	0.5931	201	0.6148	0.6484	0.6312	128	0.6121	0.7172	0.6605	198	0.6970	0.8042	0.7468	143	0.6438	0.6982	0.6699	497	0.6197	0.6776	0.6473	214	0.8390	0.8887	0.8631	1689	0.7333	0.6972	0.7148	142	0.7443	0.815	0.7780	200	0.7217	0.7876	0.7532	372	0.7113	0.7568	0.7333	407	0.6682	0.6522	0.6601	667	0.7136	0.7009	0.7072	224	0.5351	0.4796	0.5058	859	0.5930	0.6259	0.6090	433	0.6112	0.5240	0.5643	603	0.7767	0.6202	0.6897	129	0.6254	0.7284	0.6730	243	0.4815	0.4815	0.4815	189	0.7654	0.8078	0.7861	307	0.7611	0.8935	0.8220	385	0.6667	0.6082	0.6361	194	0.7828	0.7990	0.7908	194	0.6692	0.6899	0.6794	129	0.5983	0.6942	0.6427	206	0.7584	0.8153	0.7858	693	0.6740	0.7052	0.6892	563	0.7006	0.7401	0.7198	0.9378
0.1224	6.0	128118	0.2275	0.8286	0.8406	0.8345	138	0.6898	0.7445	0.7161	227	0.6013	0.7252	0.6574	131	0.7574	0.8415	0.7972	1722	0.7400	0.7483	0.7441	719	0.8084	0.8491	0.8282	159	0.7055	0.5721	0.6319	201	0.6061	0.625	0.6154	128	0.7090	0.6768	0.6925	198	0.7868	0.7483	0.7670	143	0.6454	0.7545	0.6957	497	0.6287	0.6963	0.6608	214	0.8548	0.8851	0.8697	1689	0.7669	0.7183	0.7418	142	0.75	0.825	0.7857	200	0.7130	0.8280	0.7662	372	0.6848	0.8059	0.7404	407	0.7112	0.6462	0.6771	667	0.7879	0.6964	0.7393	224	0.5378	0.5378	0.5378	859	0.6554	0.5797	0.6152	433	0.5946	0.5887	0.5917	603	0.8131	0.6744	0.7373	129	0.6483	0.7737	0.7054	243	0.5537	0.5185	0.5355	189	0.7704	0.7980	0.784	307	0.8415	0.8961	0.8679	385	0.6566	0.6701	0.6633	194	0.7879	0.8041	0.7959	194	0.6159	0.7829	0.6894	129	0.5887	0.7087	0.6432	206	0.7864	0.8023	0.7943	693	0.7388	0.6732	0.7045	563	0.7221	0.7475	0.7346	0.9406
0.0964	7.0	149471	0.2456	0.7947	0.8696	0.8304	138	0.7107	0.7577	0.7335	227	0.6522	0.6870	0.6691	131	0.7780	0.8182	0.7976	1722	0.7546	0.7483	0.7514	719	0.7870	0.8365	0.8110	159	0.6020	0.6020	0.6020	201	0.58	0.6797	0.6259	128	0.6129	0.7677	0.6816	198	0.7468	0.8252	0.7841	143	0.6642	0.7284	0.6948	497	0.6840	0.6776	0.6808	214	0.8586	0.8810	0.8697	1689	0.7836	0.7394	0.7609	142	0.7082	0.825	0.7621	200	0.7731	0.7876	0.7803	372	0.7606	0.7494	0.7550	407	0.6726	0.6837	0.6781	667	0.7581	0.7277	0.7426	224	0.5176	0.5634	0.5396	859	0.6599	0.6005	0.6288	433	0.5938	0.5672	0.5802	603	0.8776	0.6667	0.7577	129	0.7198	0.7613	0.74	243	0.5078	0.5185	0.5131	189	0.7933	0.7752	0.7842	307	0.8033	0.8909	0.8448	385	0.6071	0.7010	0.6507	194	0.7429	0.8041	0.7723	194	0.7321	0.6357	0.6805	129	0.5775	0.7233	0.6422	206	0.7858	0.7994	0.7926	693	0.6678	0.7282	0.6967	563	0.7199	0.7475	0.7334	0.9403
0.0838	8.0	170824	0.2562	0.7722	0.8841	0.8243	138	0.6929	0.7753	0.7318	227	0.6483	0.7176	0.6812	131	0.7859	0.8101	0.7978	1722	0.7419	0.7316	0.7367	719	0.7389	0.8365	0.7847	159	0.5797	0.5970	0.5882	201	0.5878	0.6797	0.6304	128	0.6574	0.7172	0.6860	198	0.7597	0.8182	0.7879	143	0.7108	0.7123	0.7116	497	0.6511	0.7150	0.6815	214	0.8791	0.8822	0.8806	1689	0.75	0.7606	0.7552	142	0.7594	0.805	0.7816	200	0.7842	0.8011	0.7926	372	0.7395	0.7813	0.7599	407	0.6965	0.6777	0.6869	667	0.7179	0.75	0.7336	224	0.5081	0.5809	0.5421	859	0.6327	0.6166	0.6246	433	0.6094	0.5821	0.5954	603	0.8776	0.6667	0.7577	129	0.7059	0.7407	0.7229	243	0.5444	0.5185	0.5312	189	0.7722	0.7948	0.7833	307	0.8067	0.8779	0.8408	385	0.6408	0.6804	0.6600	194	0.7546	0.8402	0.7951	194	0.6831	0.7519	0.7159	129	0.6255	0.7136	0.6667	206	0.7392	0.8427	0.7876	693	0.7289	0.7069	0.7178	563	0.7242	0.7514	0.7376	0.9414
0.0753	9.0	192177	0.2708	0.8026	0.8841	0.8414	138	0.7054	0.8018	0.7505	227	0.6277	0.6565	0.6418	131	0.7762	0.8380	0.8059	1722	0.7552	0.7552	0.7552	719	0.7701	0.8428	0.8048	159	0.6610	0.5821	0.6190	201	0.5915	0.6562	0.6222	128	0.6575	0.7273	0.6906	198	0.7887	0.7832	0.7860	143	0.7050	0.7163	0.7106	497	0.6270	0.7383	0.6781	214	0.8441	0.8881	0.8656	1689	0.7589	0.7535	0.7562	142	0.7125	0.855	0.7773	200	0.755	0.8118	0.7824	372	0.7512	0.8010	0.7753	407	0.6788	0.6972	0.6879	667	0.7830	0.7411	0.7615	224	0.5155	0.5821	0.5467	859	0.6386	0.6490	0.6438	433	0.6629	0.5804	0.6189	603	0.8598	0.7132	0.7797	129	0.6667	0.7490	0.7054	243	0.4787	0.5344	0.505	189	0.7610	0.7883	0.7744	307	0.8285	0.8909	0.8586	385	0.7027	0.6701	0.6860	194	0.7778	0.8299	0.8030	194	0.6923	0.7674	0.7279	129	0.6396	0.6893	0.6636	206	0.7879	0.8095	0.7986	693	0.7110	0.7123	0.7116	563	0.7258	0.7593	0.7422	0.9424
0.0574	10.0	213530	0.2862	0.8	0.8986	0.8464	138	0.7375	0.7797	0.7580	227	0.6471	0.6718	0.6592	131	0.7831	0.8008	0.7918	1722	0.6997	0.7747	0.7353	719	0.7714	0.8491	0.8084	159	0.6091	0.5970	0.6030	201	0.6357	0.6406	0.6381	128	0.7	0.7071	0.7035	198	0.7436	0.8112	0.7759	143	0.6729	0.7243	0.6977	497	0.6830	0.7150	0.6986	214	0.8627	0.8857	0.8741	1689	0.7483	0.7535	0.7509	142	0.7611	0.86	0.8075	200	0.7846	0.8226	0.8031	372	0.7640	0.7715	0.7677	407	0.6921	0.6942	0.6931	667	0.7478	0.7545	0.7511	224	0.5079	0.5960	0.5485	859	0.6457	0.6397	0.6427	433	0.6223	0.5821	0.6015	603	0.8704	0.7287	0.7932	129	0.7041	0.7737	0.7373	243	0.5073	0.5503	0.5279	189	0.7680	0.7980	0.7827	307	0.8658	0.8883	0.8769	385	0.7111	0.6598	0.6845	194	0.7681	0.8196	0.7930	194	0.7197	0.7364	0.7280	129	0.6192	0.7184	0.6652	206	0.7922	0.8196	0.8057	693	0.7206	0.7194	0.72	563	0.7282	0.7572	0.7424	0.9424
0.0568	11.0	234883	0.2951	0.8026	0.8841	0.8414	138	0.7458	0.7753	0.7603	227	0.6241	0.6718	0.6471	131	0.7737	0.8240	0.7981	1722	0.7646	0.7455	0.7549	719	0.8121	0.8428	0.8272	159	0.6685	0.5920	0.6280	201	0.6870	0.6172	0.6502	128	0.7150	0.6970	0.7059	198	0.7872	0.7762	0.7817	143	0.6631	0.7485	0.7032	497	0.6842	0.6682	0.6761	214	0.8594	0.8828	0.8709	1689	0.7863	0.7254	0.7546	142	0.7824	0.845	0.8125	200	0.7628	0.8038	0.7827	372	0.7664	0.7740	0.7702	407	0.7232	0.6777	0.6997	667	0.7820	0.7366	0.7586	224	0.5362	0.5949	0.5640	859	0.6306	0.6467	0.6385	433	0.6472	0.5871	0.6157	603	0.8857	0.7209	0.7949	129	0.7138	0.7901	0.7500	243	0.5075	0.5397	0.5231	189	0.7834	0.8013	0.7923	307	0.8561	0.8961	0.8756	385	0.6809	0.6598	0.6702	194	0.7656	0.8247	0.7940	194	0.6736	0.7519	0.7106	129	0.6262	0.6505	0.6381	206	0.7892	0.8211	0.8048	693	0.7561	0.7105	0.7326	563	0.7390	0.7548	0.7468	0.9431
0.0465	12.0	256236	0.3103	0.8194	0.9203	0.8669	138	0.7031	0.7930	0.7453	227	0.5867	0.6718	0.6263	131	0.7829	0.8211	0.8016	1722	0.7582	0.7413	0.7496	719	0.8059	0.8616	0.8328	159	0.6648	0.5920	0.6263	201	0.6385	0.6484	0.6434	128	0.6827	0.7172	0.6995	198	0.7778	0.8322	0.8041	143	0.6679	0.7324	0.6987	497	0.6864	0.7056	0.6959	214	0.8473	0.8905	0.8684	1689	0.7552	0.7606	0.7579	142	0.7362	0.865	0.7954	200	0.7487	0.8011	0.7740	372	0.7470	0.7764	0.7614	407	0.7042	0.7031	0.7037	667	0.7435	0.7634	0.7533	224	0.5438	0.5856	0.5639	859	0.6261	0.6536	0.6395	433	0.6442	0.6186	0.6311	603	0.8482	0.7364	0.7884	129	0.7283	0.7613	0.7445	243	0.5075	0.5397	0.5231	189	0.7915	0.7915	0.7915	307	0.8564	0.8987	0.8771	385	0.6211	0.7268	0.6698	194	0.7633	0.8144	0.7880	194	0.7313	0.7597	0.7452	129	0.6450	0.7233	0.6819	206	0.7758	0.8139	0.7944	693	0.7189	0.7176	0.7182	563	0.7312	0.7621	0.7464	0.9428
0.0459	13.0	277589	0.3141	0.8267	0.8986	0.8611	138	0.7254	0.7797	0.7516	227	0.6099	0.6565	0.6324	131	0.7929	0.8182	0.8054	1722	0.7562	0.7677	0.7619	719	0.8084	0.8491	0.8282	159	0.6302	0.6020	0.6158	201	0.6412	0.6562	0.6486	128	0.6931	0.7071	0.7000	198	0.7770	0.8042	0.7904	143	0.6834	0.7384	0.7099	497	0.6967	0.6869	0.6918	214	0.8631	0.8845	0.8737	1689	0.7939	0.7324	0.7619	142	0.7830	0.83	0.8058	200	0.7822	0.8011	0.7915	372	0.7482	0.7740	0.7609	407	0.6982	0.6972	0.6977	667	0.7867	0.7411	0.7632	224	0.5323	0.5856	0.5576	859	0.6469	0.6559	0.6514	433	0.6512	0.6036	0.6265	603	0.8611	0.7209	0.7848	129	0.7287	0.7737	0.7505	243	0.5185	0.5185	0.5185	189	0.7910	0.8013	0.7961	307	0.8715	0.8987	0.8849	385	0.7283	0.6907	0.7090	194	0.7512	0.7938	0.7719	194	0.7313	0.7597	0.7452	129	0.6147	0.6893	0.6499	206	0.7947	0.8268	0.8105	693	0.7170	0.7247	0.7208	563	0.7406	0.7588	0.7496	0.9436
0.0386	14.0	298942	0.3268	0.8333	0.9058	0.8681	138	0.7092	0.7841	0.7448	227	0.6028	0.6489	0.625	131	0.7848	0.8153	0.7998	1722	0.7701	0.7594	0.7647	719	0.8047	0.8553	0.8293	159	0.6373	0.6119	0.6244	201	0.6204	0.6641	0.6415	128	0.6794	0.7172	0.6978	198	0.7986	0.8042	0.8014	143	0.6691	0.7324	0.6993	497	0.7109	0.7009	0.7059	214	0.8624	0.8834	0.8728	1689	0.7754	0.7535	0.7643	142	0.7757	0.83	0.8019	200	0.7712	0.8065	0.7884	372	0.7621	0.7715	0.7668	407	0.6782	0.7076	0.6926	667	0.7661	0.7455	0.7557	224	0.5417	0.5669	0.5540	859	0.6388	0.6536	0.6461	433	0.6160	0.6119	0.6140	603	0.8889	0.7442	0.8101	129	0.7431	0.7737	0.7581	243	0.5025	0.5397	0.5204	189	0.7915	0.7915	0.7915	307	0.8618	0.8909	0.8761	385	0.6699	0.7113	0.6900	194	0.7621	0.8093	0.7850	194	0.7226	0.7674	0.7444	129	0.6384	0.6942	0.6651	206	0.7872	0.8167	0.8017	693	0.7140	0.7229	0.7184	563	0.7358	0.7585	0.7470	0.9435
0.037	15.0	320295	0.3308	0.8117	0.9058	0.8562	138	0.716	0.7885	0.7505	227	0.6028	0.6489	0.625	131	0.7838	0.8252	0.8040	1722	0.7835	0.7552	0.7691	719	0.7953	0.8553	0.8242	159	0.6630	0.5970	0.6283	201	0.6296	0.6641	0.6464	128	0.6961	0.7172	0.7065	198	0.8	0.8112	0.8056	143	0.6849	0.7304	0.7069	497	0.7156	0.7056	0.7106	214	0.8631	0.8845	0.8737	1689	0.7852	0.7465	0.7653	142	0.7602	0.84	0.7981	200	0.7601	0.8091	0.7839	372	0.7506	0.7617	0.7561	407	0.6943	0.7151	0.7046	667	0.7767	0.7455	0.7608	224	0.5351	0.5588	0.5467	859	0.6453	0.6513	0.6483	433	0.6277	0.6153	0.6214	603	0.8981	0.7519	0.8186	129	0.7362	0.7695	0.7525	243	0.5178	0.5397	0.5285	189	0.7806	0.7883	0.7844	307	0.8804	0.8987	0.8895	385	0.6863	0.7216	0.7035	194	0.7696	0.8093	0.7889	194	0.7333	0.7674	0.7500	129	0.6471	0.6942	0.6698	206	0.7917	0.8225	0.8068	693	0.7255	0.7229	0.7242	563	0.7404	0.7600	0.7501	0.9437

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.12.1+cu113
Datasets 2.7.1
Tokenizers 0.13.2

Task: Token Classification
Library: transformers
Type: deberta-v2
License: mit
Created: Dec 1, 2022
Updated: Dec 3, 2022