mistral-rand

megha-shroff/mistral-rand

mistral-rand is a machine learning model from megha-shroff. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.

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

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Hugging Face

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At a glance

Library: peft
License: apache-2.0
Access: Public
Created: Jan 18, 2024
Updated: Jan 18, 2024
SHA: 508d4a45

Base models

TheBloke/Mistral-7B-v0.1-GPTQ

Model card

From the Hugging Face model README

mistral-rand

This model is a fine-tuned version of TheBloke/Mistral-7B-v0.1-GPTQ on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4471

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: cosine
num_epochs: 15
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.7543	0.03	50	0.9190
0.8445	0.05	100	0.7860
0.7819	0.07	150	0.7460
0.7231	0.1	200	0.7147
0.6985	0.12	250	0.6924
0.6887	0.15	300	0.6823
0.6836	0.17	350	0.6702
0.6624	0.2	400	0.6574
0.6712	0.23	450	0.6507
0.6354	0.25	500	0.6417
0.6089	0.28	550	0.6373
0.6236	0.3	600	0.6284
0.6161	0.33	650	0.6228
0.6367	0.35	700	0.6152
0.6329	0.38	750	0.6097
0.5944	0.4	800	0.6076
0.6036	0.42	850	0.6030
0.5767	0.45	900	0.5989
0.6079	0.47	950	0.5954
0.5915	0.5	1000	0.5916
0.5911	0.53	1050	0.5859
0.5752	0.55	1100	0.5847
0.5698	0.57	1150	0.5802
0.5813	0.6	1200	0.5754
0.5918	0.62	1250	0.5735
0.5587	0.65	1300	0.5677
0.5933	0.68	1350	0.5620
0.5262	0.7	1400	0.5522
0.5455	0.72	1450	0.5457
0.5472	0.75	1500	0.5416
0.536	0.78	1550	0.5400
0.527	0.8	1600	0.5393
0.5516	0.82	1650	0.5350
0.5578	0.85	1700	0.5356
0.5501	0.88	1750	0.5297
0.5316	0.9	1800	0.5288
0.5436	0.93	1850	0.5268
0.514	0.95	1900	0.5295
0.5249	0.97	1950	0.5246
0.538	1.0	2000	0.5226
0.4967	1.02	2050	0.5237
0.4991	1.05	2100	0.5261
0.5142	1.07	2150	0.5203
0.4891	1.1	2200	0.5174
0.5058	1.12	2250	0.5173
0.4895	1.15	2300	0.5182
0.4918	1.18	2350	0.5139
0.485	1.2	2400	0.5091
0.5173	1.23	2450	0.5121
0.5021	1.25	2500	0.5116
0.4834	1.27	2550	0.5097
0.4754	1.3	2600	0.5137
0.4907	1.32	2650	0.5059
0.5155	1.35	2700	0.5051
0.4965	1.38	2750	0.5050
0.5148	1.4	2800	0.5043
0.4709	1.43	2850	0.5032
0.4864	1.45	2900	0.5037
0.4794	1.48	2950	0.5029
0.4803	1.5	3000	0.5012
0.4843	1.52	3050	0.5017
0.4726	1.55	3100	0.4984
0.4773	1.57	3150	0.4968
0.4673	1.6	3200	0.4995
0.4803	1.62	3250	0.4990
0.4926	1.65	3300	0.4965
0.4814	1.68	3350	0.4973
0.4714	1.7	3400	0.4930
0.4797	1.73	3450	0.4903
0.4807	1.75	3500	0.4932
0.4815	1.77	3550	0.4888
0.4852	1.8	3600	0.4874
0.4802	1.82	3650	0.4887
0.4701	1.85	3700	0.4897
0.4572	1.88	3750	0.4873
0.4469	1.9	3800	0.4878
0.478	1.93	3850	0.4885
0.4449	1.95	3900	0.4866
0.4634	1.98	3950	0.4843
0.4718	2.0	4000	0.4838
0.4458	2.02	4050	0.4822
0.461	2.05	4100	0.4801
0.4247	2.08	4150	0.4856
0.4325	2.1	4200	0.4830
0.4354	2.12	4250	0.4827
0.4313	2.15	4300	0.4807
0.4753	2.17	4350	0.4812
0.4442	2.2	4400	0.4833
0.4431	2.23	4450	0.4851
0.4485	2.25	4500	0.4815
0.4416	2.27	4550	0.4813
0.4613	2.3	4600	0.4777
0.4121	2.33	4650	0.4775
0.4311	2.35	4700	0.4768
0.4532	2.38	4750	0.4765
0.4342	2.4	4800	0.4781
0.4189	2.42	4850	0.4743
0.443	2.45	4900	0.4742
0.4596	2.48	4950	0.4734
0.4193	2.5	5000	0.4719
0.4321	2.52	5050	0.4723
0.4456	2.55	5100	0.4713
0.4464	2.58	5150	0.4694
0.4273	2.6	5200	0.4700
0.4239	2.62	5250	0.4701
0.4282	2.65	5300	0.4687
0.4303	2.67	5350	0.4686
0.4559	2.7	5400	0.4695
0.4542	2.73	5450	0.4692
0.4532	2.75	5500	0.4685
0.4505	2.77	5550	0.4663
0.4533	2.8	5600	0.4660
0.4351	2.83	5650	0.4640
0.4354	2.85	5700	0.4651
0.4374	2.88	5750	0.4664
0.4571	2.9	5800	0.4662
0.4663	2.92	5850	0.4636
0.4211	2.95	5900	0.4645
0.4349	2.98	5950	0.4622
0.4167	3.0	6000	0.4634
0.4176	3.02	6050	0.4621
0.4387	3.05	6100	0.4607
0.395	3.08	6150	0.4638
0.4186	3.1	6200	0.4623
0.3993	3.12	6250	0.4622
0.4009	3.15	6300	0.4631
0.4033	3.17	6350	0.4640
0.389	3.2	6400	0.4662
0.4037	3.23	6450	0.4618
0.4287	3.25	6500	0.4617
0.3917	3.27	6550	0.4611
0.3944	3.3	6600	0.4626
0.4088	3.33	6650	0.4622
0.4205	3.35	6700	0.4604
0.4273	3.38	6750	0.4608
0.4139	3.4	6800	0.4607
0.3888	3.42	6850	0.4603
0.4353	3.45	6900	0.4573
0.4222	3.48	6950	0.4577
0.4083	3.5	7000	0.4571
0.4161	3.52	7050	0.4560
0.3879	3.55	7100	0.4540
0.3819	3.58	7150	0.4570
0.4345	3.6	7200	0.4551
0.4101	3.62	7250	0.4569
0.4194	3.65	7300	0.4543
0.4066	3.67	7350	0.4563
0.4144	3.7	7400	0.4553
0.4134	3.73	7450	0.4566
0.3906	3.75	7500	0.4550
0.4128	3.77	7550	0.4546
0.4227	3.8	7600	0.4535
0.4069	3.83	7650	0.4517
0.3927	3.85	7700	0.4548
0.3977	3.88	7750	0.4521
0.4184	3.9	7800	0.4516
0.3854	3.92	7850	0.4513
0.4129	3.95	7900	0.4524
0.3998	3.98	7950	0.4548
0.4227	4.0	8000	0.4534
0.3788	4.03	8050	0.4520
0.3732	4.05	8100	0.4501
0.375	4.08	8150	0.4565
0.3845	4.1	8200	0.4515
0.378	4.12	8250	0.4492
0.3874	4.15	8300	0.4508
0.3802	4.17	8350	0.4510
0.3596	4.2	8400	0.4524
0.4009	4.22	8450	0.4549
0.4105	4.25	8500	0.4515
0.3716	4.28	8550	0.4508
0.3673	4.3	8600	0.4497
0.3882	4.33	8650	0.4513
0.375	4.35	8700	0.4524
0.3654	4.38	8750	0.4503
0.3983	4.4	8800	0.4509
0.4067	4.42	8850	0.4487
0.3966	4.45	8900	0.4519
0.378	4.47	8950	0.4505
0.3755	4.5	9000	0.4508
0.3855	4.53	9050	0.4500
0.3938	4.55	9100	0.4527
0.3946	4.58	9150	0.4531
0.3752	4.6	9200	0.4506
0.3723	4.62	9250	0.4459
0.3704	4.65	9300	0.4467
0.3861	4.67	9350	0.4484
0.3965	4.7	9400	0.4481
0.3972	4.72	9450	0.4482
0.3917	4.75	9500	0.4447
0.3688	4.78	9550	0.4473
0.3861	4.8	9600	0.4491
0.3593	4.83	9650	0.4491
0.3916	4.85	9700	0.4432
0.3748	4.88	9750	0.4432
0.3921	4.9	9800	0.4459
0.3745	4.92	9850	0.4457
0.4002	4.95	9900	0.4443
0.3767	4.97	9950	0.4430
0.3537	5.0	10000	0.4470
0.3673	5.03	10050	0.4531
0.3506	5.05	10100	0.4474
0.3506	5.08	10150	0.4497
0.3622	5.1	10200	0.4471

Framework versions

PEFT 0.7.1
Transformers 4.36.2
Pytorch 2.1.2+cu121
Datasets 2.16.1
Tokenizers 0.15.0

Library: peft
License: apache-2.0
Created: Jan 18, 2024
Updated: Jan 18, 2024