zephyr-Me

HimashaJ96/zephyr-Me

zephyr-Me is a machine learning model from HimashaJ96. 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 mit.

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

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Hugging Face

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.safetensors109 MB · 98%

At a glance

Library: peft
License: mit
Access: Public
Created: Dec 27, 2023
Updated: Dec 27, 2023
SHA: 8c351780

Base models

TheBloke/zephyr-7B-beta-GPTQ

Model card

From the Hugging Face model README

zephyr-Me

This model is a fine-tuned version of TheBloke/zephyr-7B-beta-GPTQ on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.0107
Rouge1: 0.7127
Rouge2: 0.4797
Rougel: 0.6694
Rougelsum: 0.6951
Meteor: 0.7003
F1 Score: 0.0010

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: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Meteor	F1 Score
2.1273	0.15	4	2.0726	0.4931	0.1866	0.4166	0.4753	0.4834	0.0077
1.6907	0.3	8	1.5193	0.6035	0.3389	0.5483	0.5905	0.5816	0.0010
1.3096	0.44	12	1.3236	0.6571	0.4159	0.6080	0.6386	0.6473	0.0008
1.1588	0.59	16	1.2651	0.6652	0.4210	0.6174	0.6455	0.6528	0.0008
1.1038	0.74	20	1.1852	0.6772	0.4239	0.6274	0.6557	0.6570	0.0008
1.0362	0.89	24	1.1448	0.6750	0.4256	0.6278	0.6547	0.6613	0.0008
1.0733	1.04	28	1.1137	0.6864	0.4397	0.6379	0.6655	0.6743	0.0008
0.8783	1.19	32	1.1179	0.6914	0.4510	0.6430	0.6680	0.6813	0.0010
0.8761	1.33	36	1.1020	0.6984	0.4545	0.6497	0.6768	0.6865	0.0010
0.8774	1.48	40	1.0696	0.7033	0.4604	0.6549	0.6834	0.6908	0.0010
0.8621	1.63	44	1.0485	0.7030	0.4642	0.6568	0.6850	0.6915	0.0010
0.8143	1.78	48	1.0334	0.7064	0.4670	0.6601	0.6874	0.6929	0.0010
0.7483	1.93	52	1.0232	0.7060	0.4681	0.6606	0.6868	0.6940	0.0010
0.7647	2.07	56	1.0148	0.7058	0.4700	0.6623	0.6884	0.6886	0.0010
0.6659	2.22	60	1.0135	0.7088	0.4737	0.6655	0.6917	0.6952	0.0010
0.7135	2.37	64	1.0098	0.7132	0.4783	0.6699	0.6948	0.6989	0.0010
0.6685	2.52	68	1.0123	0.7116	0.4787	0.6687	0.6939	0.6995	0.0010
0.6538	2.67	72	1.0113	0.7145	0.4811	0.6705	0.6966	0.7030	0.0010
0.6648	2.81	76	1.0108	0.7132	0.4800	0.6694	0.6955	0.7011	0.0010
0.6278	2.96	80	1.0107	0.7127	0.4797	0.6694	0.6951	0.7003	0.0010

Framework versions

PEFT 0.7.1
Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.0
Tokenizers 0.15.0

Library: peft
License: mit
Created: Dec 27, 2023
Updated: Dec 27, 2023