deberta-v3-base-finetuned-mrpc

RazyDave/deberta-v3-base-finetuned-mrpc

deberta-v3-base-finetuned-mrpc is a text classification model from RazyDave. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.

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

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At a glance

Task: Text Classification
Library: transformers
License: mit
Model type: deberta-v2
Access: Public
Created: Dec 16, 2022
Updated: Dec 16, 2022
SHA: 5491e8b4

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Datasets

glue

Model card

From the Hugging Face model README

deberta-v3-base-finetuned-mrpc

This model is a fine-tuned version of microsoft/deberta-v3-base on the glue dataset. It achieves the following results on the evaluation set:

Loss: 0.3297
Accuracy: 0.8922
F1: 0.9241

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: 16
eval_batch_size: 16
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	Validation Loss	Accuracy	F1
No log	1.0	230	0.3411	0.8725	0.9081
No log	2.0	460	0.3297	0.8922	0.9241
0.3727	3.0	690	0.4133	0.8922	0.9236
0.3727	4.0	920	0.5315	0.8848	0.9174
0.1068	5.0	1150	0.5898	0.8848	0.9171

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.7.1
Tokenizers 0.13.2

Task: Text Classification
Library: transformers
Type: deberta-v2
License: mit
Created: Dec 16, 2022
Updated: Dec 16, 2022