model_segment_content_DEFI

phunganhsang/model_segment_content_DEFI

model_segment_content_DEFI is a text classification model from phunganhsang. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as agpl-3.0.

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

Downloads · 30 days

26% of all-time downloads

All-time downloads

Public

Parameters

135M

540 MB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors540 MB · 100%

At a glance

Task: Text Classification
Library: transformers
License: agpl-3.0
Model type: roberta
Access: Public
Created: Jun 22, 2026
Updated: Jun 22, 2026
SHA: c98c9e2a

Try a prompt

Base models

vinai/phobert-base-v2

Model card

From the Hugging Face model README

model_segment_content_DEFI

This model is a fine-tuned version of vinai/phobert-base-v2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1130
Accuracy: 0.9707
F1: 0.9659

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	0.1419	150	0.1087	0.9636	0.9580
No log	0.2838	300	0.0979	0.9671	0.9620
No log	0.4257	450	0.0967	0.9614	0.9559
No log	0.5676	600	0.0894	0.9688	0.9639
No log	0.7096	750	0.0917	0.9693	0.9644
No log	0.8515	900	0.0967	0.9672	0.9617
No log	0.9934	1050	0.0939	0.9693	0.9643
0.1071	1.1353	1200	0.0852	0.9697	0.9651
0.1071	1.2772	1350	0.0914	0.9705	0.9659
0.1071	1.4191	1500	0.0870	0.9706	0.9658
0.1071	1.5610	1650	0.0908	0.9707	0.9659
0.1071	1.7029	1800	0.0873	0.9707	0.9662
0.1071	1.8448	1950	0.1037	0.9699	0.9654
0.1071	1.9868	2100	0.0829	0.9716	0.9673
0.0675	2.1287	2250	0.1106	0.9686	0.9640
0.0675	2.2706	2400	0.0950	0.9716	0.9672
0.0675	2.4125	2550	0.0900	0.9712	0.9666
0.0675	2.5544	2700	0.0904	0.9723	0.9678
0.0675	2.6963	2850	0.1167	0.9669	0.9621
0.0675	2.8382	3000	0.0909	0.9694	0.9649
0.0675	2.9801	3150	0.1014	0.9687	0.9640
0.0506	3.1220	3300	0.1003	0.9720	0.9675
0.0506	3.2640	3450	0.1130	0.9707	0.9659

Framework versions

Transformers 5.12.1
Pytorch 2.7.1+cu118
Datasets 5.0.0
Tokenizers 0.22.2

Task: Text Classification
Library: transformers
Type: roberta
License: agpl-3.0
Created: Jun 22, 2026
Updated: Jun 22, 2026