LiLT-RE

SriDoc/LiLT-RE

LiLT-RE is a machine learning model from SriDoc. 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. The card lists the license as mit.

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

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Hugging Face

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At a glance

Library: transformers
License: mit
Model type: lilt
Access: Public
Created: Mar 29, 2024
Updated: Mar 29, 2024
SHA: 6dd64a84

Base models

kavg/LiLT-RE-IT

Datasets

xfun

Model card

From the Hugging Face model README

checkpoints

This model is a fine-tuned version of kavg/LiLT-RE-IT on the xfun dataset. It achieves the following results on the evaluation set:

Precision: 0.4898
Recall: 0.6641
F1: 0.5638
Loss: 0.6049

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: 1e-05
train_batch_size: 8
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
training_steps: 10000

Training results

Training Loss	Epoch	Step	F1	Validation Loss	Precision	Recall
0.061	41.67	500	0.4764	0.2580	0.4142	0.5606
0.0332	83.33	1000	0.4906	0.3439	0.4181	0.5934
0.0264	125.0	1500	0.5194	0.3892	0.4436	0.6263
0.0104	166.67	2000	0.5250	0.4165	0.4468	0.6364
0.0064	208.33	2500	0.5245	0.4479	0.4460	0.6364
0.0013	250.0	3000	0.5204	0.4655	0.4532	0.6111
0.0019	291.67	3500	0.5342	0.4859	0.4630	0.6313
0.0009	333.33	4000	0.5420	0.5162	0.4640	0.6515
0.0006	375.0	4500	0.5515	0.5724	0.4795	0.6490
0.0039	416.67	5000	0.5470	0.5687	0.4662	0.6616
0.0012	458.33	5500	0.5595	0.5582	0.4860	0.6591
0.0001	500.0	6000	0.5730	0.5709	0.4981	0.6742
0.0022	541.67	6500	0.5578	0.5795	0.4877	0.6515
0.0012	583.33	7000	0.5674	0.5710	0.4953	0.6641
0.0009	625.0	7500	0.5607	0.5994	0.4879	0.6591
0.0002	666.67	8000	0.5616	0.5865	0.4879	0.6616
0.0016	708.33	8500	0.4972	0.6717	0.5714	0.5878
0.0	750.0	9000	0.4898	0.6641	0.5638	0.6049
0.0002	791.67	9500	0.4826	0.6641	0.5590	0.6223
0.0014	833.33	10000	0.4890	0.6742	0.5669	0.6318

Framework versions

Transformers 4.38.2
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.1

Library: transformers
Type: lilt
License: mit
Created: Mar 29, 2024
Updated: Mar 29, 2024