PhobertLexicalMeta

gechim/PhobertLexicalMeta

PhobertLexicalMeta 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. It is set up for transformers.

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

Downloads · 30 days

16% of all-time downloads

All-time downloads

144

Public

Parameters

269M

1.1 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors1.1 GB · 100%

At a glance

Library: transformers
Access: Public
Created: Jul 24, 2024
Updated: Jul 29, 2024
SHA: 87cf048c

Base models

gechim/metadata-cls-no-gov-8k-v3

Model card

From the Hugging Face model README

PhobertLexicalMeta

This model is a fine-tuned version of gechim/metadata-cls-no-gov-8k-v3 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0927
Accuracy: 0.9792
F1: 0.9664

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
0.1701	1.9608	200	0.0936	0.9741	0.9575
0.0537	3.9216	400	0.0780	0.9780	0.9647
0.0252	5.8824	600	0.0762	0.9805	0.9687
0.016	7.8431	800	0.0996	0.9780	0.9640
0.0098	9.8039	1000	0.0927	0.9792	0.9664

Framework versions

Transformers 4.43.1
Pytorch 2.1.2
Datasets 2.20.0
Tokenizers 0.19.1

Library: transformers
Created: Jul 24, 2024
Updated: Jul 29, 2024