Llama-2-7b-QLoRA-01

onuralp/Llama-2-7b-QLoRA-01

Llama-2-7b-QLoRA-01 is a text generation model from onuralp. 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. --

Downloads · 30 days

19% of all-time downloads

All-time downloads

Public

Repo size

2.9 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.pt1.9 GB · 60%

At a glance

Task: Text Generation
Library: transformers
Model type: llama
Access: Public
Created: Oct 26, 2023
Updated: Oct 26, 2023
SHA: 8a3fa8c3

Try a prompt

Base models

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

Model card

From the Hugging Face model README

qlora-out

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: 0.6420

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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
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
0.9758	0.03	20	0.6870
0.7228	0.06	40	0.6791
0.6804	0.09	60	0.6613
0.8117	0.11	80	0.6360
0.6458	0.14	100	0.6335
0.7509	0.17	120	0.6245
0.6174	0.2	140	0.6313
0.7549	0.23	160	0.6180
0.6015	0.26	180	0.6167
0.716	0.29	200	0.6165
0.6304	0.31	220	0.6014
0.5781	0.34	240	0.6107
0.8	0.37	260	0.5949
0.6845	0.4	280	0.5953
0.5857	0.43	300	0.5940
0.6369	0.46	320	0.5889
0.4767	0.49	340	0.5946
0.4848	0.52	360	0.5991
0.9067	0.54	380	0.5943
0.5943	0.57	400	0.5854
0.6999	0.6	420	0.5941
0.5173	0.63	440	0.5887
0.4201	0.66	460	0.5952
0.667	0.69	480	0.5802
0.8568	0.72	500	0.5922
0.515	0.74	520	0.5800
0.504	0.77	540	0.5894
0.6361	0.8	560	0.5983
0.4896	0.83	580	0.5770
0.6044	0.86	600	0.5717
0.4925	0.89	620	0.5715
0.4704	0.92	640	0.5707
0.5342	0.94	660	0.5748
0.755	0.97	680	0.5673
0.6547	1.0	700	0.5721
0.6014	1.03	720	0.5892
0.4692	1.06	740	0.5981
0.407	1.09	760	0.5995
0.5351	1.12	780	0.5948
0.3004	1.14	800	0.5758
0.554	1.17	820	0.5862
0.6394	1.2	840	0.5850
0.7135	1.23	860	0.5900
0.6323	1.26	880	0.5931
0.3257	1.29	900	0.5902
0.5183	1.32	920	0.5763
0.5383	1.34	940	0.5842
0.453	1.37	960	0.5878
0.5305	1.4	980	0.5975
0.4316	1.43	1000	0.5829
0.5992	1.46	1020	0.5801
0.5043	1.49	1040	0.5731
0.4566	1.52	1060	0.5777
0.4879	1.55	1080	0.5785
0.7149	1.57	1100	0.5727
0.4555	1.6	1120	0.5824
0.5248	1.63	1140	0.5821
0.4981	1.66	1160	0.5711
0.5595	1.69	1180	0.5931
0.577	1.72	1200	0.5898
0.3202	1.75	1220	0.5775
0.7182	1.77	1240	0.5800
0.5608	1.8	1260	0.5668
0.5677	1.83	1280	0.5797
0.5046	1.86	1300	0.5725
0.5165	1.89	1320	0.5709
0.6432	1.92	1340	0.5817
0.4973	1.95	1360	0.5695
0.2903	1.97	1380	0.5762
0.3099	2.0	1400	0.5832
0.4383	2.03	1420	0.6773
0.287	2.06	1440	0.6324
0.3395	2.09	1460	0.6600
0.2677	2.12	1480	0.6409
0.4145	2.15	1500	0.6259
0.2435	2.17	1520	0.6528
0.2539	2.2	1540	0.6379
0.3619	2.23	1560	0.6402
0.3289	2.26	1580	0.6355
0.4993	2.29	1600	0.6515
0.2705	2.32	1620	0.6357
0.4863	2.35	1640	0.6385
0.356	2.37	1660	0.6364
0.3433	2.4	1680	0.6390
0.3215	2.43	1700	0.6325
0.4795	2.46	1720	0.6336
0.3457	2.49	1740	0.6342
0.6864	2.52	1760	0.6435
0.3965	2.55	1780	0.6447
0.3424	2.58	1800	0.6344
0.7203	2.6	1820	0.6385
0.6209	2.63	1840	0.6475
0.3693	2.66	1860	0.6439
0.4004	2.69	1880	0.6410
0.3499	2.72	1900	0.6392
0.4691	2.75	1920	0.6396
0.2775	2.78	1940	0.6387
0.26	2.8	1960	0.6423
0.2917	2.83	1980	0.6432
0.4461	2.86	2000	0.6414
0.4149	2.89	2020	0.6433
0.2863	2.92	2040	0.6428
0.1832	2.95	2060	0.6424
0.5409	2.98	2080	0.6420

Framework versions

Transformers 4.34.1
Pytorch 2.0.1+cu118
Datasets 2.14.6
Tokenizers 0.14.1

Task: Text Generation
Library: transformers
Type: llama
Created: Oct 26, 2023
Updated: Oct 26, 2023