deberta-v3-base-finetuned-rte

RazyDave/deberta-v3-base-finetuned-rte

deberta-v3-base-finetuned-rte 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. --

Downloads · 30 days

1% of all-time downloads

All-time downloads

546

Public

Repo size

2.2 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin738 MB · 99%

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: 3cf615cc

Try a prompt

Datasets

glue

Model card

From the Hugging Face model README

deberta-v3-base-finetuned-rte

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: 0.8234
Accuracy: 0.8195

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
No log	1.0	156	0.5610	0.7545
No log	2.0	312	0.6270	0.7617
No log	3.0	468	0.6565	0.7906
0.3919	4.0	624	0.8234	0.8195
0.3919	5.0	780	0.9628	0.7978

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