layoutlmv3-finetuned-DocLayNet

This model is a fine-tuned version of microsoft/layoutlmv3-base on the doc_lay_net-small dataset. It achieves the following results on the evaluation set:

• Loss: 0.5644
• Precision: 0.6179
• Recall: 0.7238
• F1: 0.6667
• Accuracy: 0.8720

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: 2
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
1.3383	0.58	200	0.8358	0.3007	0.4381	0.3566	0.7724
0.8308	1.16	400	0.6735	0.4634	0.5429	0.5	0.8084
0.518	1.74	600	0.5706	0.5373	0.6857	0.6025	0.8399
0.3856	2.33	800	0.6303	0.6032	0.7238	0.6580	0.8648
0.2558	2.91	1000	0.5644	0.6179	0.7238	0.6667	0.8720

Framework versions

• Transformers 4.27.3
• Pytorch 1.13.1+cu116
• Datasets 2.10.1
• Tokenizers 0.13.2

How to Train & Inference:

Check this out this repo: https://github.com/mit1280/Document-AI