nids_med

stephen-steckler/nids_med

nids_med is a text generation model from stephen-steckler. Use it when you need the model to write or continue text. It is set up for transformers.

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

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At a glance

Task: Text Generation
Library: transformers
Model type: llama
Access: Public
Created: Nov 16, 2023
Updated: Nov 16, 2023
SHA: fb60e3a5

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Base models

meta-llama/Llama-2-7b-hf

Model card

From the Hugging Face model README

mid-nids

This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0342

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: 0.0002
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 2
total_train_batch_size: 8
total_eval_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 10
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
0.0682	0.03	20	0.0982
0.0895	0.06	40	0.0792
0.015	0.09	60	0.0405
0.0376	0.11	80	0.0357
0.0196	0.14	100	0.0342
0.0219	0.17	120	0.0334
0.0188	0.2	140	0.0317
0.0147	0.23	160	0.0365
0.0224	0.26	180	0.0388
0.0116	0.28	200	0.0504
0.0158	0.31	220	0.0692
0.0193	0.34	240	0.0407
0.0181	0.37	260	0.0443
0.0124	0.4	280	0.0482
0.0094	0.43	300	0.0549
0.0081	0.46	320	0.0341
0.0188	0.48	340	0.0401
0.021	0.51	360	0.0508
0.0125	0.54	380	0.0409
0.0071	0.57	400	0.0424
0.0165	0.6	420	0.0566
0.0075	0.63	440	0.0537
0.0096	0.65	460	0.0338
0.012	0.68	480	0.0489
0.0041	0.71	500	0.0442
0.0012	0.74	520	0.0439
0.0096	0.77	540	0.0381
0.005	0.8	560	0.0449
0.0239	0.83	580	0.0452
0.0166	0.85	600	0.0383
0.0081	0.88	620	0.0249
0.0166	0.91	640	0.0442
0.0106	0.94	660	0.0327
0.0161	0.97	680	0.0386
0.0038	1.0	700	0.0377
0.0029	1.02	720	0.0367
0.0164	1.05	740	0.0276
0.0128	1.08	760	0.0259
0.0108	1.11	780	0.0294
0.026	1.14	800	0.0285
0.0104	1.17	820	0.0297
0.0102	1.19	840	0.0271
0.0111	1.22	860	0.0293
0.0088	1.25	880	0.0305
0.0116	1.28	900	0.0250
0.0066	1.31	920	0.0442
0.0061	1.34	940	0.0309
0.0173	1.37	960	0.0231
0.0032	1.39	980	0.0230
0.0119	1.42	1000	0.0401
0.0083	1.45	1020	0.0274
0.0047	1.48	1040	0.0359
0.0221	1.51	1060	0.0301
0.0038	1.54	1080	0.0280
0.0052	1.56	1100	0.0235
0.0084	1.59	1120	0.0323
0.012	1.62	1140	0.0320
0.0019	1.65	1160	0.0256
0.0175	1.68	1180	0.0300
0.0078	1.71	1200	0.0362
0.0088	1.74	1220	0.0310
0.0065	1.76	1240	0.0301
0.0059	1.79	1260	0.0348
0.0066	1.82	1280	0.0341
0.0015	1.85	1300	0.0280
0.0091	1.88	1320	0.0266
0.0053	1.91	1340	0.0350
0.0077	1.93	1360	0.0333
0.0081	1.96	1380	0.0320
0.0129	1.99	1400	0.0391
0.0082	2.02	1420	0.0388
0.008	2.05	1440	0.0212
0.0025	2.08	1460	0.0362
0.0006	2.11	1480	0.0289
0.0034	2.13	1500	0.0347
0.0115	2.16	1520	0.0313
0.0061	2.19	1540	0.0297
0.0065	2.22	1560	0.0335
0.0144	2.25	1580	0.0379
0.0075	2.28	1600	0.0300
0.0093	2.3	1620	0.0322
0.0091	2.33	1640	0.0313
0.0051	2.36	1660	0.0278
0.0046	2.39	1680	0.0294
0.0004	2.42	1700	0.0283
0.0054	2.45	1720	0.0296
0.0034	2.48	1740	0.0337
0.0065	2.5	1760	0.0341
0.0034	2.53	1780	0.0345
0.0114	2.56	1800	0.0371
0.0044	2.59	1820	0.0377
0.0086	2.62	1840	0.0344
0.0065	2.65	1860	0.0332
0.0051	2.67	1880	0.0344
0.008	2.7	1900	0.0355
0.0035	2.73	1920	0.0351
0.0065	2.76	1940	0.0352
0.0097	2.79	1960	0.0347
0.0034	2.82	1980	0.0347
0.0054	2.84	2000	0.0348
0.0045	2.87	2020	0.0344
0.0032	2.9	2040	0.0343
0.0072	2.93	2060	0.0342
0.0074	2.96	2080	0.0344
0.0111	2.99	2100	0.0342

Framework versions

Transformers 4.34.1
Pytorch 2.0.1+cu117
Datasets 2.14.6
Tokenizers 0.14.1

Task: Text Generation
Library: transformers
Type: llama
Created: Nov 16, 2023
Updated: Nov 16, 2023