metadata-cls-no-gov-8k-vnnic

gechim/metadata-cls-no-gov-8k-vnnic

metadata-cls-no-gov-8k-vnnic is a machine learning model from gechim. Use it for the machine learning task on the model card, and read the license before you ship it in a product.

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

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At a glance

Model type: roberta
Access: Public
Created: Aug 10, 2024
Updated: Aug 10, 2024
SHA: ffdd82ee

Base models

vinai/phobert-base-v2

Model card

From the Hugging Face model README

metadata-cls-no-gov-8k-vnnic

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: 0.2819
Accuracy: 0.9319
F1: 0.7796

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.5853	1.1364	150	0.2434	0.9311	0.7583
0.2425	2.2727	300	0.2510	0.9251	0.7630
0.1714	3.4091	450	0.2222	0.9345	0.7682
0.1274	4.5455	600	0.2391	0.9328	0.7862
0.1075	5.6818	750	0.2507	0.9319	0.7732
0.0867	6.8182	900	0.2808	0.9277	0.7711
0.0625	7.9545	1050	0.2965	0.9243	0.7674
0.0539	9.0909	1200	0.2819	0.9319	0.7796

Framework versions

Transformers 4.44.0
Pytorch 2.1.2
Datasets 2.20.0
Tokenizers 0.19.1

Type: roberta
Created: Aug 10, 2024
Updated: Aug 10, 2024