deberta-v3-base-finetuned-m_help_seller

Gregorig/deberta-v3-base-finetuned-m_help_seller

deberta-v3-base-finetuned-m_help_seller is a text classification model from Gregorig. 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: Jun 5, 2024
Updated: Jun 5, 2024
SHA: c1a8eaa6

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Base models

microsoft/deberta-v3-base

Model card

From the Hugging Face model README

deberta-v3-base-finetuned-m_help_seller

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

Loss: 0.2102
Accuracy: 0.965
F1: 0.9680

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: 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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6889	1.0	26	0.6581	0.945	0.9266
0.5816	2.0	52	0.3887	0.925	0.9376
0.4027	3.0	78	0.2345	0.95	0.9561
0.2698	4.0	104	0.2011	0.965	0.9680
0.1968	5.0	130	0.2102	0.965	0.9680

Framework versions

Transformers 4.41.1
Pytorch 2.3.0+cu121
Tokenizers 0.19.1

Task: Text Classification
Library: transformers
Type: deberta-v2
License: mit
Created: Jun 5, 2024
Updated: Jun 5, 2024