eliascc5's picture
layoutlmv3-finetuned-FUNSD
90672ba verified
|
raw
history blame
2.4 kB
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: layoutlmv3-finetuned-FUNSD
    results: []

layoutlmv3-finetuned-FUNSD

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: 0.6088
  • Precision: 0.9024
  • Recall: 0.9190
  • F1: 0.9107
  • Accuracy: 0.8544

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 0.6659 0.7835 0.8217 0.8021 0.7825
No log 2.67 200 0.5631 0.8229 0.8912 0.8557 0.7903
No log 4.0 300 0.4653 0.8470 0.8992 0.8723 0.8389
No log 5.33 400 0.5080 0.8526 0.9081 0.8795 0.8324
0.5612 6.67 500 0.5200 0.8733 0.9036 0.8882 0.8429
0.5612 8.0 600 0.5480 0.8878 0.9160 0.9017 0.8531
0.5612 9.33 700 0.5655 0.8894 0.9146 0.9018 0.8521
0.5612 10.67 800 0.5971 0.8943 0.9160 0.9050 0.8514
0.5612 12.0 900 0.5873 0.9022 0.9215 0.9118 0.8583
0.1425 13.33 1000 0.6088 0.9024 0.9190 0.9107 0.8544

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1