STS-Lora-Fine-Tuning-Capstone-roberta-base-deepset-filtered-115-with-higher-r-mid

rajevan123/STS-Lora-Fine-Tuning-Capstone-roberta-base-deepset-filtered-115-with-higher-r-mid

STS-Lora-Fine-Tuning-Capstone-roberta-base-deepset-filtered-115-with-higher-r-mid is a machine learning model from rajevan123. 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 cc-by-4.0.

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: cc-by-4.0
Access: Public
Created: Mar 28, 2024
Updated: Mar 28, 2024
SHA: ee90e519

Base models

deepset/roberta-base-squad2

Model card

From the Hugging Face model README

STS-Lora-Fine-Tuning-Capstone-roberta-base-deepset-filtered-115-with-higher-r-mid

This model is a fine-tuned version of deepset/roberta-base-squad2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.9056
Accuracy: 0.6040

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: 3e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	76	1.2568	0.4161
No log	2.0	152	1.1655	0.4603
No log	3.0	228	1.0574	0.5120
No log	4.0	304	0.9846	0.5574
No log	5.0	380	0.9665	0.5675
No log	6.0	456	0.9544	0.5738
1.0456	7.0	532	0.9503	0.5763
1.0456	8.0	608	0.9269	0.5876
1.0456	9.0	684	0.9233	0.5889
1.0456	10.0	760	0.9264	0.5927
1.0456	11.0	836	0.9092	0.5927
1.0456	12.0	912	0.9187	0.5914
1.0456	13.0	988	0.9122	0.6003
0.8486	14.0	1064	0.9091	0.5977
0.8486	15.0	1140	0.9079	0.5965
0.8486	16.0	1216	0.9144	0.5952
0.8486	17.0	1292	0.9049	0.5977
0.8486	18.0	1368	0.9257	0.5939
0.8486	19.0	1444	0.9006	0.5952
0.8112	20.0	1520	0.9008	0.6015
0.8112	21.0	1596	0.9044	0.6040
0.8112	22.0	1672	0.9008	0.6053
0.8112	23.0	1748	0.9052	0.6028
0.8112	24.0	1824	0.9065	0.6028
0.8112	25.0	1900	0.9015	0.6053
0.8112	26.0	1976	0.9141	0.5965
0.7992	27.0	2052	0.9072	0.6053
0.7992	28.0	2128	0.9042	0.6053
0.7992	29.0	2204	0.9054	0.6040
0.7992	30.0	2280	0.9056	0.6040

Framework versions

PEFT 0.10.0
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Library: peft
License: cc-by-4.0
Created: Mar 28, 2024
Updated: Mar 28, 2024