layout3 / README.md
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metadata
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: layout3
    results: []

layout3

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

  • Loss: 0.6334
  • Precision: 0.8935
  • Recall: 0.9131
  • F1: 0.9032
  • Accuracy: 0.8586

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: 2
  • 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
No log 1.33 100 0.6874 0.7820 0.8073 0.7944 0.7841
No log 2.67 200 0.4485 0.8321 0.8838 0.8571 0.8474
No log 4.0 300 0.4403 0.8579 0.9086 0.8825 0.8414
No log 5.33 400 0.4593 0.8452 0.9056 0.8743 0.8341
0.5531 6.67 500 0.4881 0.8732 0.9170 0.8946 0.8575
0.5531 8.0 600 0.5332 0.8761 0.9101 0.8928 0.8547
0.5531 9.33 700 0.5910 0.8894 0.9106 0.8999 0.8517
0.5531 10.67 800 0.5914 0.8909 0.9131 0.9019 0.8557
0.5531 12.0 900 0.6127 0.9001 0.9180 0.9090 0.8614
0.1245 13.33 1000 0.6334 0.8935 0.9131 0.9032 0.8586

Framework versions

  • Transformers 4.32.0
  • Pytorch 2.0.0+cu118
  • Datasets 2.17.1
  • Tokenizers 0.13.2