mainCut-label9

chihun-jang/mainCut-label9

mainCut-label9 is a text classification model from chihun-jang. 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: roberta
Access: Public
Created: Oct 12, 2023
Updated: Oct 12, 2023
SHA: aaa42e56

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Base models

klue/roberta-small

Model card

From the Hugging Face model README

mainCut-label9

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

Loss: 1.1075
Accuracy: 0.6309

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.2286	0.4	500	1.2054	0.5685
1.2387	0.8	1000	1.1320	0.6062
0.9892	1.2	1500	1.1341	0.6169
1.1259	1.6	2000	1.1117	0.6202
0.9904	2.0	2500	1.0929	0.6262
1.0053	2.4	3000	1.1021	0.6243
0.9492	2.8	3500	1.0982	0.6251
0.9811	3.2	4000	1.1167	0.6238
0.9258	3.6	4500	1.1068	0.6341
0.8481	4.0	5000	1.1075	0.6309

Framework versions

Transformers 4.32.1
Pytorch 2.0.1
Datasets 2.14.4
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: roberta
Created: Oct 12, 2023
Updated: Oct 12, 2023