phobert-v2_v2

aiface/phobert-v2_v2

phobert-v2_v2 is a text classification model from aiface. 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. --

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At a glance

Task: Text Classification
Library: transformers
License: agpl-3.0
Model type: roberta
Access: Public
Created: Aug 12, 2025
Updated: Aug 12, 2025
SHA: 82c23a59

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Base models

vinai/phobert-base-v2

Model card

From the Hugging Face model README

phobert-v2_v2

This model is a fine-tuned version of vinai/phobert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3130
Accuracy: 0.9507
Precision Macro: 0.8904
Recall Macro: 0.8541
F1 Macro: 0.8704
F1 Weighted: 0.9497

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: 3e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 128
optimizer: Use 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: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision Macro	Recall Macro	F1 Macro	F1 Weighted
0.4636	1.0	90	0.2180	0.9419	0.9099	0.7652	0.8049	0.9359
0.1882	2.0	180	0.1916	0.9419	0.8351	0.8649	0.8485	0.9433
0.1453	3.0	270	0.1898	0.9488	0.8743	0.8402	0.8555	0.9476
0.1175	4.0	360	0.1932	0.9526	0.9141	0.8267	0.8597	0.9500
0.0856	5.0	450	0.2092	0.9514	0.8708	0.8711	0.8709	0.9514
0.0826	6.0	540	0.2221	0.9526	0.9063	0.8516	0.8748	0.9512
0.0675	7.0	630	0.2342	0.9438	0.8419	0.8696	0.8545	0.9450
0.0618	8.0	720	0.2402	0.9469	0.8890	0.8430	0.8630	0.9456
0.0426	9.0	810	0.2503	0.9507	0.8797	0.8543	0.8660	0.9499
0.038	10.0	900	0.2786	0.9514	0.8999	0.8467	0.8692	0.9499
0.039	11.0	990	0.2795	0.9463	0.8628	0.8554	0.8589	0.9460
0.0263	12.0	1080	0.2817	0.9488	0.8733	0.8571	0.8648	0.9483
0.0209	13.0	1170	0.2840	0.9495	0.8802	0.8576	0.8681	0.9488
0.0221	14.0	1260	0.2769	0.9526	0.8904	0.8639	0.8761	0.9519
0.0172	15.0	1350	0.2861	0.9514	0.8985	0.8546	0.8739	0.9502
0.0159	16.0	1440	0.3031	0.9482	0.8850	0.8523	0.8671	0.9472
0.0124	17.0	1530	0.3119	0.9501	0.8792	0.8538	0.8655	0.9493
0.0107	18.0	1620	0.3173	0.9476	0.8948	0.8476	0.8681	0.9463
0.0106	19.0	1710	0.3094	0.9545	0.8979	0.8611	0.8776	0.9535
0.0108	20.0	1800	0.3130	0.9507	0.8904	0.8541	0.8704	0.9497

Framework versions

Transformers 4.55.0
Pytorch 2.7.0+cu126
Datasets 4.0.0
Tokenizers 0.21.4

Task: Text Classification
Library: transformers
Type: roberta
License: agpl-3.0
Created: Aug 12, 2025
Updated: Aug 12, 2025