Edit model card

layoutlmv3-er-ner

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

  • Loss: 0.2025
  • Precision: 0.6442
  • Recall: 0.6761
  • F1: 0.6598
  • Accuracy: 0.9507

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 22 0.2940 0.4214 0.2956 0.3475 0.9147
No log 2.0 44 0.2487 0.4134 0.4526 0.4321 0.9175
No log 3.0 66 0.1922 0.5399 0.5460 0.5429 0.9392
No log 4.0 88 0.1977 0.5653 0.5813 0.5732 0.9434
No log 5.0 110 0.2018 0.6173 0.6252 0.6212 0.9477
No log 6.0 132 0.1823 0.6232 0.6153 0.6192 0.9485
No log 7.0 154 0.1972 0.6203 0.6238 0.6220 0.9477
No log 8.0 176 0.1952 0.6292 0.6407 0.6349 0.9511
No log 9.0 198 0.2070 0.6331 0.6492 0.6411 0.9489
No log 10.0 220 0.2025 0.6442 0.6761 0.6598 0.9507

Framework versions

  • Transformers 4.20.0.dev0
  • Pytorch 1.11.0
  • Datasets 2.1.0
  • Tokenizers 0.12.1
Downloads last month
25
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.