LiLT-RE-DE-SIN

kavg/LiLT-RE-DE-SIN

LiLT-RE-DE-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

15% 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: 6e9b0c3f

Base models

kavg/LiLT-RE-DE

Datasets

xfun

Model card

From the Hugging Face model README

checkpoints

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

Precision: 0.2952
Recall: 0.4167
F1: 0.3455
Loss: 0.3186

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	Precision	Recall	F1	Validation Loss
0.1035	41.67	500	0.2905	0.1540	0.2013	0.2291
0.0691	83.33	1000	0.2952	0.4167	0.3455	0.3186
0.0442	125.0	1500	0.2970	0.5909	0.3953	0.2765
0.024	166.67	2000	0.3227	0.5884	0.4168	0.4144
0.0216	208.33	2500	0.3234	0.6035	0.4211	0.4036
0.0096	250.0	3000	0.3534	0.6364	0.4545	0.5716
0.0079	291.67	3500	0.3456	0.5934	0.4368	0.6643
0.0045	333.33	4000	0.3427	0.6187	0.4410	0.6955
0.0017	375.0	4500	0.3587	0.6187	0.4541	0.8144
0.0147	416.67	5000	0.3407	0.6212	0.4401	0.8101
0.0027	458.33	5500	0.3491	0.6162	0.4457	0.8809
0.0079	500.0	6000	0.3183	0.6061	0.4174	0.8863
0.0028	541.67	6500	0.3506	0.5985	0.4422	0.9944
0.0075	583.33	7000	0.3476	0.5960	0.4391	0.9920
0.0002	625.0	7500	0.3448	0.6061	0.4396	0.9752
0.0025	666.67	8000	0.3456	0.6162	0.4428	0.9866
0.0037	708.33	8500	0.3465	0.6187	0.4442	1.0153
0.0041	750.0	9000	0.3442	0.6136	0.4410	1.1227
0.0023	791.67	9500	0.3450	0.6237	0.4442	1.0995
0.0007	833.33	10000	0.3408	0.6162	0.4388	1.1097

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