eng_cate

tangminhanh/eng_cate

eng_cate is a text classification model from tangminhanh. 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: Jul 30, 2024
Updated: Jul 30, 2024
SHA: b84a1b4c

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Base models

microsoft/deberta-v3-small

Model card

From the Hugging Face model README

eng_cate

This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2466
Accuracy: 0.9159
F1: 0.9159
Precision: 0.9159
Recall: 0.9159

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: 32
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	Precision	Recall
No log	1.0	54	0.3248	0.9159	0.9159	0.9159	0.9159
No log	2.0	108	0.2950	0.9159	0.9159	0.9159	0.9159
No log	3.0	162	0.2577	0.9159	0.9159	0.9159	0.9159
No log	4.0	216	0.2557	0.9159	0.9159	0.9159	0.9159
No log	5.0	270	0.2466	0.9159	0.9159	0.9159	0.9159

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

Task: Text Classification
Library: transformers
Type: deberta-v2
License: mit
Created: Jul 30, 2024
Updated: Jul 30, 2024