QWEN_2_7B_Fact_U

rishavranaut/QWEN_2_7B_Fact_U

QWEN_2_7B_Fact_U is a machine learning model from rishavranaut. 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. --

Downloads · 30 days

26% of all-time downloads

All-time downloads

Public

Repo size

809 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors40.4 MB · 78%

At a glance

Library: peft
License: apache-2.0
Access: Public
Created: Sep 25, 2024
Updated: Sep 26, 2024
SHA: a3562ec3

Base models

Qwen/Qwen2-7B

Model card

From the Hugging Face model README

QWEN_2_7B_Fact_U

This model is a fine-tuned version of Qwen/Qwen2-7B on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.0739
Accuracy: 0.7812
Precision: 0.8033
Recall: 0.7670
F1 score: 0.7847

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: 0.0001
train_batch_size: 8
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Accuracy	F1 score	Precision	Recall	Validation Loss
0.9778	0.2509	200	0.6529	0.7128	0.6256	0.8281	0.8856
0.8085	0.5019	400	0.7376	0.7514	0.7407	0.7624	0.7247
0.728	0.7528	600	0.7541	0.7628	0.7654	0.7602	0.6549
0.6569	1.0038	800	0.6584	0.7671	0.7891	0.7534	0.7708
0.4831	1.2547	1000	0.7161	0.7118	0.6756	0.8575	0.7557
0.4952	1.5056	1200	0.6699	0.7788	0.7848	0.7919	0.7883
0.4992	1.7566	1400	0.6185	0.7824	0.8173	0.7489	0.7816
0.4104	2.0075	1600	0.6325	0.7753	0.7770	0.7964	0.7866
0.3071	2.2585	1800	0.6979	0.7635	0.7796	0.7602	0.7698
0.3557	2.5094	2000	0.7270	0.7694	0.7617	0.8100	0.7851
0.3088	2.7604	2200	0.7186	0.7788	0.8024	0.7624	0.7819
0.3848	3.0113	2400	0.6926	0.7718	0.7857	0.7715	0.7785
0.2186	3.2622	2600	0.7965	0.7835	0.8225	0.7443	0.7815
0.2531	3.5132	2800	0.7843	0.78	0.8364	0.7172	0.7722
0.2134	3.7641	3000	0.7977	0.7729	0.7849	0.7760	0.7804
0.1961	4.0151	3200	0.8438	0.7871	0.8443	0.7240	0.7795
0.1464	4.2660	3400	0.9256	0.7835	0.8225	0.7443	0.7815
0.1132	4.5169	3600	1.0431	0.7824	0.8052	0.7670	0.7856
0.1323	4.7679	3800	1.0739	0.7812	0.8033	0.7670	0.7847

Framework versions

PEFT 0.11.1
Transformers 4.44.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

Library: peft
License: apache-2.0
Created: Sep 25, 2024
Updated: Sep 26, 2024