docket-language-model

scales-okn/docket-language-model

docket-language-model is a fill-mask model from scales-okn. Use it when you need the model to fill a missing word. It is set up for transformers. The card lists the license as gpl-3.0.

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

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At a glance

Task: Fill-Mask
Library: transformers
License: gpl-3.0
Model type: deberta-v2
Access: Public
Created: Jun 4, 2022
Updated: Apr 15, 2025
SHA: 68ca752e

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Model card

From the Hugging Face model README

deberta-v3-large-ddlm

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

Loss: 0.5241

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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 64
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.9823	0.01	1000	0.9163
0.8817	0.02	2000	0.9022
0.9647	0.03	3000	0.8879
0.8646	0.04	4000	0.8577
0.9159	0.06	5000	0.8677
0.8449	0.07	6000	0.8221
0.8681	0.08	7000	0.8332
0.8738	0.09	8000	0.8334
0.8638	0.1	9000	0.8236
0.9066	0.11	10000	0.8200
0.8686	0.12	11000	0.8092
0.7736	0.13	12000	0.8199
0.8054	0.14	13000	0.7972
0.8934	0.16	14000	0.7998
0.7884	0.17	15000	0.7895
0.8278	0.18	16000	0.7586
0.8482	0.19	17000	0.7562
0.8716	0.2	18000	0.7819
0.8881	0.21	19000	0.7878
0.8397	0.22	20000	0.7989
0.811	0.23	21000	0.7846
0.7762	0.24	22000	0.7753
0.7778	0.25	23000	0.7878
0.737	0.27	24000	0.7473
0.8451	0.28	25000	0.7460
0.823	0.29	26000	0.7300
0.7472	0.3	27000	0.7292
0.8048	0.31	28000	0.7697
0.7962	0.32	29000	0.7359
0.8048	0.33	30000	0.7409
0.8095	0.34	31000	0.7434
0.7451	0.35	32000	0.7534
0.6997	0.37	33000	0.7602
0.8116	0.38	34000	0.7566
0.7963	0.39	35000	0.7245
0.786	0.4	36000	0.7311
0.7991	0.41	37000	0.7230
0.723	0.42	38000	0.7209
0.789	0.43	39000	0.7418
0.7296	0.44	40000	0.7325
0.7363	0.45	41000	0.7134
0.758	0.47	42000	0.6948
0.711	0.48	43000	0.6992
0.7984	0.49	44000	0.7055
0.8402	0.5	45000	0.7108
0.8553	0.51	46000	0.7005
0.7538	0.52	47000	0.7208
0.7169	0.53	48000	0.7291
0.7345	0.54	49000	0.7195
0.758	0.55	50000	0.6694
0.7868	0.56	51000	0.6938
0.6966	0.58	52000	0.6867
0.7389	0.59	53000	0.6862
0.7529	0.6	54000	0.7175
0.7345	0.61	55000	0.6970
0.766	0.62	56000	0.7017
0.7043	0.63	57000	0.6916
0.6474	0.64	58000	0.7129
0.7456	0.65	59000	0.6802
0.7512	0.66	60000	0.6951
0.6816	0.68	61000	0.7072
0.7206	0.69	62000	0.6967
0.6439	0.7	63000	0.6798
0.7309	0.71	64000	0.7163
0.6925	0.72	65000	0.6794
0.6833	0.73	66000	0.6637
0.6643	0.74	67000	0.6855
0.6433	0.75	68000	0.7035
0.7595	0.76	69000	0.7008
0.7214	0.78	70000	0.6618
0.7111	0.79	71000	0.6850
0.7375	0.8	72000	0.6909
0.6779	0.81	73000	0.7042
0.6646	0.82	74000	0.6634
0.6616	0.83	75000	0.7020
0.6762	0.84	76000	0.6638
0.7509	0.85	77000	0.6541
0.6963	0.86	78000	0.6781
0.6949	0.87	79000	0.6576
0.6781	0.89	80000	0.6900
0.65	0.9	81000	0.6835
0.7205	0.91	82000	0.6712
0.6901	0.92	83000	0.6699
0.6972	0.93	84000	0.6456
0.7041	0.94	85000	0.6497
0.6864	0.95	86000	0.6432
0.7308	0.96	87000	0.6497
0.6886	0.97	88000	0.6674
0.6947	0.99	89000	0.6638
0.6567	1.0	90000	0.6242
0.7185	1.01	91000	0.6704
0.7435	1.02	92000	0.6681
0.7108	1.03	93000	0.6619
0.6942	1.04	94000	0.6306
0.6998	1.05	95000	0.6409
0.6481	1.06	96000	0.6476
0.727	1.07	97000	0.6354
0.647	1.09	98000	0.6222
0.6622	1.1	99000	0.6119
0.6346	1.11	100000	0.6471
0.6203	1.12	101000	0.6655
0.6765	1.13	102000	0.6473
0.6703	1.14	103000	0.6308
0.6793	1.15	104000	0.6531
0.683	1.16	105000	0.6693
0.6654	1.17	106000	0.6241
0.6626	1.18	107000	0.6215
0.6976	1.2	108000	0.6479
0.7494	1.21	109000	0.6345
0.691	1.22	110000	0.6322
0.6568	1.23	111000	0.6265
0.705	1.24	112000	0.6281
0.6307	1.25	113000	0.6202
0.6828	1.26	114000	0.6158
0.6403	1.27	115000	0.6495
0.6615	1.28	116000	0.6298
0.6237	1.3	117000	0.6234
0.6707	1.31	118000	0.6267
0.6823	1.32	119000	0.6299
0.6333	1.33	120000	0.6169
0.685	1.34	121000	0.6371
0.6941	1.35	122000	0.6245
0.6358	1.36	123000	0.6291
0.6754	1.37	124000	0.6400
0.6286	1.38	125000	0.6148
0.7036	1.4	126000	0.6033
0.645	1.41	127000	0.6295
0.6578	1.42	128000	0.6348
0.651	1.43	129000	0.6222
0.5558	1.44	130000	0.6231
0.6601	1.45	131000	0.6302
0.6304	1.46	132000	0.6127
0.6177	1.47	133000	0.6047
0.5933	1.48	134000	0.6169
0.6307	1.49	135000	0.6012
0.6018	1.51	136000	0.5900
0.6724	1.52	137000	0.6086
0.6367	1.53	138000	0.6414
0.6515	1.54	139000	0.6267
0.5902	1.55	140000	0.5913
0.6523	1.56	141000	0.5992
0.6005	1.57	142000	0.6128
0.6179	1.58	143000	0.6089
0.6154	1.59	144000	0.6353
0.6298	1.61	145000	0.5997
0.5623	1.62	146000	0.5974
0.5787	1.63	147000	0.6165
0.6099	1.64	148000	0.6246
0.658	1.65	149000	0.6116
0.6567	1.66	150000	0.5938
0.6227	1.67	151000	0.5948
0.5858	1.68	152000	0.5822
0.6227	1.69	153000	0.5802
0.6699	1.71	154000	0.6067
0.5989	1.72	155000	0.6073
0.6184	1.73	156000	0.6124
0.6404	1.74	157000	0.6169
0.639	1.75	158000	0.5997
0.6433	1.76	159000	0.5989
0.5574	1.77	160000	0.5796
0.5983	1.78	161000	0.6036
0.6532	1.79	162000	0.5888
0.6679	1.8	163000	0.6038
0.62	1.82	164000	0.5984
0.5541	1.83	165000	0.6003
0.6192	1.84	166000	0.5786
0.6613	1.85	167000	0.6064
0.5923	1.86	168000	0.6018
0.5894	1.87	169000	0.5912
0.6462	1.88	170000	0.5902
0.5811	1.89	171000	0.6030
0.6358	1.9	172000	0.5915
0.614	1.92	173000	0.5886
0.5969	1.93	174000	0.6084
0.6146	1.94	175000	0.6003
0.6051	1.95	176000	0.5835
0.6268	1.96	177000	0.5999
0.6436	1.97	178000	0.5965
0.6167	1.98	179000	0.5789
0.5647	1.99	180000	0.5669
0.6038	2.0	181000	0.6009
0.6082	2.02	182000	0.5799
0.6483	2.03	183000	0.5716
0.5503	2.04	184000	0.5806
0.6231	2.05	185000	0.5699
0.5892	2.06	186000	0.5979
0.5933	2.07	187000	0.5709
0.594	2.08	188000	0.5719
0.5838	2.09	189000	0.5879
0.6039	2.1	190000	0.5984
0.5911	2.11	191000	0.5953
0.563	2.13	192000	0.5772
0.5671	2.14	193000	0.5771
0.6051	2.15	194000	0.5972
0.5852	2.16	195000	0.5917
0.5757	2.17	196000	0.5819
0.6557	2.18	197000	0.5655
0.6055	2.19	198000	0.5820
0.6067	2.2	199000	0.5801
0.6422	2.21	200000	0.5590
0.624	2.23	201000	0.5573
0.6222	2.24	202000	0.5661
0.5597	2.25	203000	0.5786
0.5746	2.26	204000	0.5622
0.6269	2.27	205000	0.5804
0.6241	2.28	206000	0.5696
0.6519	2.29	207000	0.5367
0.6161	2.3	208000	0.5666
0.5415	2.31	209000	0.5633
0.633	2.33	210000	0.5499
0.5566	2.34	211000	0.5822
0.6158	2.35	212000	0.5826
0.5574	2.36	213000	0.5429
0.5748	2.37	214000	0.5736
0.5818	2.38	215000	0.5599
0.6226	2.39	216000	0.5407
0.5733	2.4	217000	0.5759
0.6268	2.41	218000	0.5725
0.5885	2.42	219000	0.5771
0.5708	2.44	220000	0.5654
0.5783	2.45	221000	0.5756
0.61	2.46	222000	0.5647
0.5848	2.47	223000	0.5532
0.5869	2.48	224000	0.5519
0.5717	2.49	225000	0.5621
0.5675	2.5	226000	0.5446
0.6321	2.51	227000	0.5812
0.568	2.52	228000	0.5673
0.5577	2.54	229000	0.5590
0.5888	2.55	230000	0.5628
0.6389	2.56	231000	0.5828
0.5782	2.57	232000	0.5543
0.5871	2.58	233000	0.5575
0.5593	2.59	234000	0.5625
0.6167	2.6	235000	0.5450
0.5828	2.61	236000	0.5627
0.5411	2.62	237000	0.5498
0.6168	2.64	238000	0.5891
0.6508	2.65	239000	0.5811
0.6322	2.66	240000	0.5649
0.6131	2.67	241000	0.5473
0.5419	2.68	242000	0.5583
0.5685	2.69	243000	0.5635
0.5267	2.7	244000	0.5481
0.5357	2.71	245000	0.5474
0.585	2.72	246000	0.5281
0.5894	2.73	247000	0.5457
0.5665	2.75	248000	0.5579
0.5409	2.76	249000	0.5412
0.6051	2.77	250000	0.5447
0.5866	2.78	251000	0.5535
0.5348	2.79	252000	0.5377
0.5606	2.8	253000	0.5524
0.5142	2.81	254000	0.5441
0.543	2.82	255000	0.5499
0.5763	2.83	256000	0.5241

Framework versions

Transformers 4.20.0.dev0
Pytorch 1.10.0+cu102
Datasets 1.15.1
Tokenizers 0.11.0

Task: Fill-Mask
Library: transformers
Type: deberta-v2
License: gpl-3.0
Created: Jun 4, 2022
Updated: Apr 15, 2025