fine-tuned-roberta-nosql-injection

ankush-003/fine-tuned-roberta-nosql-injection

fine-tuned-roberta-nosql-injection is a fill-mask model from ankush-003. Use it when you need the model to fill a missing word. 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: Fill-Mask
Library: transformers
License: mit
Model type: roberta
Access: Public
Created: Jul 18, 2023
Updated: Jul 18, 2023
SHA: ec4f26b4

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Base models

Model card

From the Hugging Face model README

fine-tuned-roberta-nosql-injection

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

Loss: 0.0000

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: 2e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 75

Training results

Training Loss	Epoch	Step	Validation Loss
1.2572	1.0	158	0.2235
0.1175	2.0	316	0.0325
0.0454	3.0	474	0.1079
0.05	4.0	632	0.0212
0.0677	5.0	790	0.0713
0.0821	6.0	948	0.0007
0.0259	7.0	1106	0.0277
0.0422	8.0	1264	0.0068
0.0282	9.0	1422	0.0492
0.0273	10.0	1580	0.0008
0.0272	11.0	1738	0.0256
0.0859	12.0	1896	0.0000
0.0271	13.0	2054	0.0001
0.0058	14.0	2212	0.0583
0.0121	15.0	2370	0.0257
0.0189	16.0	2528	0.0631
0.0275	17.0	2686	0.0186
0.006	18.0	2844	0.0027
0.025	19.0	3002	0.0349
0.0377	20.0	3160	0.0004
0.0108	21.0	3318	0.0091
0.0233	22.0	3476	0.0772
0.0216	23.0	3634	0.0000
0.0255	24.0	3792	0.0607
0.0211	25.0	3950	0.0251
0.037	26.0	4108	0.0223
0.0057	27.0	4266	0.0375
0.0464	28.0	4424	0.0659
0.0446	29.0	4582	0.0235
0.0453	30.0	4740	0.0278
0.0033	31.0	4898	0.0417
0.0104	32.0	5056	0.0544
0.0084	33.0	5214	0.0000
0.0004	34.0	5372	0.0247
0.0185	35.0	5530	0.0002
0.0165	36.0	5688	0.0000
0.0381	37.0	5846	0.0000
0.0281	38.0	6004	0.0000
0.006	39.0	6162	0.0085
0.0083	40.0	6320	0.0000
0.0101	41.0	6478	0.0006
0.0282	42.0	6636	0.0003
0.0202	43.0	6794	0.0205
0.0053	44.0	6952	0.0275
0.0293	45.0	7110	0.0485
0.0119	46.0	7268	0.0000
0.0045	47.0	7426	0.0000
0.0066	48.0	7584	0.0268
0.0191	49.0	7742	0.0103
0.0007	50.0	7900	0.0386
0.0072	51.0	8058	0.0000
0.0031	52.0	8216	0.0000
0.0037	53.0	8374	0.0225
0.0135	54.0	8532	0.0003
0.0015	55.0	8690	0.0002
0.0066	56.0	8848	0.0025
0.0281	57.0	9006	0.0145
0.012	58.0	9164	0.0000
0.0065	59.0	9322	0.0000
0.0054	60.0	9480	0.0082
0.0104	61.0	9638	0.0000
0.0005	62.0	9796	0.0303
0.005	63.0	9954	0.0000
0.0092	64.0	10112	0.0412
0.0055	65.0	10270	0.0191
0.0092	66.0	10428	0.0158
0.0065	67.0	10586	0.0087
0.0004	68.0	10744	0.0000
0.0068	69.0	10902	0.0044
0.0043	70.0	11060	0.0022
0.0055	71.0	11218	0.0009
0.0063	72.0	11376	0.0000
0.0022	73.0	11534	0.0006
0.0116	74.0	11692	0.0014
0.0043	75.0	11850	0.0000

Framework versions

Transformers 4.31.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.11.0

Task: Fill-Mask
Library: transformers
Type: roberta
License: mit
Created: Jul 18, 2023
Updated: Jul 18, 2023