non-material-charges-extraction

PixelPulse64/non-material-charges-extraction

non-material-charges-extraction is a token classification model from PixelPulse64. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as cc-by-nc-sa-4.0.

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

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At a glance

Task: Token Classification
Library: transformers
License: cc-by-nc-sa-4.0
Model type: layoutlmv3
Access: Public
Created: Oct 15, 2025
Updated: Oct 18, 2025
SHA: 32c9d163

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Base models

microsoft/layoutlmv3-large

Model card

From the Hugging Face model README

non-material-charges-extraction

This model is a fine-tuned version of microsoft/layoutlmv3-large on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1490

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: 1
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	45	0.1515
No log	2.0	90	0.1526
No log	3.0	135	0.1490

Framework versions

Transformers 4.57.1
Pytorch 2.9.0+cu130
Datasets 4.2.0
Tokenizers 0.22.1

Task: Token Classification
Library: transformers
Type: layoutlmv3
License: cc-by-nc-sa-4.0
Created: Oct 15, 2025
Updated: Oct 18, 2025