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agentlans/bge-small-en-v1.5-prompt-quality

sourceHugging Facemitupdated 16d agoView on Hugging Face

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bge-small-en-v1.5-quality

This model is a fine-tuned version of BAAI/bge-small-en-v1.5 on the agentlans/prompt-quality dataset. It achieves the following results on the evaluation set:

—Loss: 1.3925
—Mse: 1.3925

Examples

Prompt	Quality
How can make the branches of a Cactus grow leaves?	-2.891
Think of something creative to do with a banana.	-3.078
List top 5 differences between men and women	-1.242
Name the popular tourist attraction in a given city. Copenhagen	-0.9883
how can an MBA applied to the field of biotech?	-1.625
How can I configure i8N for reports developed in TIBCO Jaspersoft server	-0.832
what are the criteria to identify who to interview when doing market research	-1.047
Do earthquake warning systems take into account potential volcanic triggers for tsunamis?	-0.4102
Make a list of items required to create a Harry Potter themed party.	-0.3574
Write a tongue twister about a quirky quail in the style of Shel Silverstein.	2.516

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

—learning_rate: 5e-05
—trainbatchsize: 8
—evalbatchsize: 8
—seed: 42
—optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
—lrschedulertype: linear
—num_epochs: 20.0

Training results

Training Loss	Epoch	Step	Validation Loss	Mse
1.7064	1.0	9976	1.5169	1.5169
1.3945	2.0	19952	1.5205	1.5205
1.0004	3.0	29928	1.3925	1.3925
0.8248	4.0	39904	1.5392	1.5392
0.6471	5.0	49880	1.5778	1.5778
0.5265	6.0	59856	1.6023	1.6023
0.4439	7.0	69832	1.6765	1.6765
0.36	8.0	79808	1.6086	1.6086
0.3072	9.0	89784	1.5445	1.5445
0.2535	10.0	99760	1.6000	1.6000
0.209	11.0	109736	1.5538	1.5538
0.1827	12.0	119712	1.5323	1.5323
0.1614	13.0	129688	1.5196	1.5196
0.133	14.0	139664	1.4935	1.4935
0.127	15.0	149640	1.5164	1.5164
0.1076	16.0	159616	1.5022	1.5022
0.0926	17.0	169592	1.4562	1.4562
0.0835	18.0	179568	1.4688	1.4688
0.0775	19.0	189544	1.4841	1.4841
0.0769	20.0	199520	1.4606	1.4606

Framework versions

—Transformers 5.0.0.dev0
—Pytorch 2.9.1+cu128
—Datasets 4.4.1
—Tokenizers 0.22.1

License

This fine-tuned model is released under the MIT License.

This model is based on BAAI/bge-small-en-v1.5, which is also licensed under the MIT License. The copyright notice and license for the base model are preserved in LICENSE.

Commercial use, modification, distribution, and private use are permitted under the terms of the MIT License.