deberta-finetuned-claimdecomp

gavulsim/deberta-finetuned-claimdecomp

deberta-finetuned-claimdecomp is a text classification model from gavulsim. 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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Hugging Face

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At a glance

Task: Text Classification
Library: transformers
License: mit
Model type: deberta
Access: Public
Created: Oct 24, 2023
Updated: Oct 24, 2023
SHA: b48485f2

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Base models

microsoft/deberta-base

Model card

From the Hugging Face model README

deberta-finetuned-claimdecomp

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

Loss: 1.7521
Accuracy: 0.205

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 30000

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.7301	50.0	5000	1.7496	0.205
1.7267	100.0	10000	1.7525	0.205
1.7277	150.0	15000	1.7508	0.205
1.7278	200.0	20000	1.7508	0.205
1.7222	250.0	25000	1.7506	0.205
1.725	300.0	30000	1.7521	0.205

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1

Task: Text Classification
Library: transformers
Type: deberta
License: mit
Created: Oct 24, 2023
Updated: Oct 24, 2023