Hugging Face's logo

scofield
/
layoutlmv3-finetuned-cord_100

Token Classification
Transformers
PyTorch
TensorBoard
layoutlmv3
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
Edit model card

layoutlmv3-finetuned-cord_100

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

  • Loss: 0.3066
  • Precision: 0.9289
  • Recall: 0.9394
  • F1: 0.9341
  • Accuracy: 0.9393

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: 5
  • eval_batch_size: 5
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 2500

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 4.17 250 0.9691 0.7365 0.7867 0.7608 0.7992
1.3706 8.33 500 0.5325 0.8645 0.8885 0.8763 0.8858
1.3706 12.5 750 0.3943 0.8939 0.9139 0.9038 0.9151
0.3211 16.67 1000 0.3364 0.9209 0.9319 0.9263 0.9342
0.3211 20.83 1250 0.3217 0.9246 0.9364 0.9305 0.9346
0.1405 25.0 1500 0.3100 0.9296 0.9394 0.9345 0.9355
0.1405 29.17 1750 0.3113 0.9275 0.9386 0.9330 0.9363
0.076 33.33 2000 0.3183 0.9280 0.9364 0.9322 0.9351
0.076 37.5 2250 0.3125 0.9211 0.9356 0.9283 0.9363
0.0549 41.67 2500 0.3066 0.9289 0.9394 0.9341 0.9393

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu116
  • Datasets 2.8.0
  • Tokenizers 0.13.2
Downloads last month
6
Inference Examples
Token Classification
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.

Evaluation results

View on Papers With Code