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

Downloads last month
67
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train Mit1208/layoutlmv3-finetuned-DocLayNet

Evaluation results