LiLT-RE-EN-SIN

kavg/LiLT-RE-EN-SIN

LiLT-RE-EN-SIN is a machine learning model from kavg. 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. --

Downloads · 30 days

29% of all-time downloads

All-time downloads

Public

Parameters

287M

1.2 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors1.1 GB · 99%

At a glance

Library: transformers
License: mit
Model type: lilt
Access: Public
Created: Mar 29, 2024
Updated: Mar 29, 2024
SHA: 61984021

Base models

kavg/LiLT-RE-EN

Datasets

xfun

Model card

From the Hugging Face model README

checkpoints

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

Precision: 0.4702
Recall: 0.5581
F1: 0.5104
Loss: 0.5301

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
0.0661	41.67	500	0.3769	0.2542	0.3360	0.4293
0.0547	83.33	1000	0.4404	0.2624	0.3805	0.5227
0.0671	125.0	1500	0.4580	0.2623	0.4031	0.5303
0.0284	166.67	2000	0.4764	0.3800	0.4142	0.5606
0.0177	208.33	2500	0.4883	0.3349	0.4371	0.5530
0.0164	250.0	3000	0.4926	0.3123	0.4491	0.5455
0.0081	291.67	3500	0.4966	0.3830	0.4458	0.5606
0.0067	333.33	4000	0.4916	0.3459	0.4424	0.5530
0.0048	375.0	4500	0.4989	0.4200	0.4527	0.5556
0.0112	416.67	5000	0.5158	0.4377	0.4672	0.5758
0.0052	458.33	5500	0.5085	0.4983	0.4619	0.5657
0.0023	500.0	6000	0.5086	0.5621	0.4654	0.5606
0.0022	541.67	6500	0.5074	0.5063	0.4635	0.5606
0.0083	583.33	7000	0.5109	0.5471	0.4693	0.5606
0.0023	625.0	7500	0.5028	0.5268	0.4559	0.5606
0.0027	666.67	8000	0.5098	0.5385	0.4674	0.5606
0.0078	708.33	8500	0.4581	0.5657	0.5062	0.5135
0.0015	750.0	9000	0.4702	0.5581	0.5104	0.5301
0.0043	791.67	9500	0.4595	0.5581	0.5040	0.5684
0.0007	833.33	10000	0.4587	0.5606	0.5045	0.5711

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