ComOM-VIDeBERTa-2

datleviet/ComOM-VIDeBERTa-2

ComOM-VIDeBERTa-2 is a text classification model from datleviet. Use it when you need a label for a piece of text. It is set up for transformers.

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

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At a glance

Task: Text Classification
Library: transformers
Model type: deberta-v2
Access: Public
Created: Dec 5, 2023
Updated: Dec 5, 2023
SHA: 2cccaa6a

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Base models

Fsoft-AIC/videberta-base

Model card

From the Hugging Face model README

ComOM-VIDeBERTa-2

This model is a fine-tuned version of Fsoft-AIC/videberta-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.3046
Accuracy: 0.5357

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: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	77	1.4249	0.4708
No log	2.0	154	1.4096	0.4708
No log	3.0	231	1.3871	0.4708
No log	4.0	308	1.3809	0.5032
No log	5.0	385	1.3529	0.5195
No log	6.0	462	1.3257	0.5260
1.4302	7.0	539	1.3101	0.5325
1.4302	8.0	616	1.3046	0.5357

Framework versions

Transformers 4.35.0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.14.1

Task: Text Classification
Library: transformers
Type: deberta-v2
Created: Dec 5, 2023
Updated: Dec 5, 2023