metadata

base_model: layoutlmv3
tags:
  - generated_from_trainer
datasets:
  - mp-02/cord
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: layoutlmv3-finetuned-cord
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: mp-02/cord
          type: mp-02/cord
        metrics:
          - name: Precision
            type: precision
            value: 0.9474485910129474
          - name: Recall
            type: recall
            value: 0.9658385093167702
          - name: F1
            type: f1
            value: 0.9565551710880431
          - name: Accuracy
            type: accuracy
            value: 0.9613752122241087

layoutlmv3-finetuned-cord

This model is a fine-tuned version of layoutlmv3 on the mp-02/cord dataset. It achieves the following results on the evaluation set:

Loss: 0.2047
Precision: 0.9474
Recall: 0.9658
F1: 0.9566
Accuracy: 0.9614

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: 10
eval_batch_size: 10
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 1500

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	3.125	250	0.7037	0.8188	0.8665	0.8419	0.8587
1.0839	6.25	500	0.3828	0.8926	0.9293	0.9106	0.9223
1.0839	9.375	750	0.2811	0.9371	0.9596	0.9482	0.9469
0.2469	12.5	1000	0.2295	0.9401	0.9620	0.9509	0.9529
0.2469	15.625	1250	0.2106	0.9460	0.9658	0.9558	0.9601
0.1263	18.75	1500	0.2047	0.9474	0.9658	0.9566	0.9614

Framework versions

Transformers 4.42.4
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1