metadata

license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
  - generated_from_trainer
datasets:
  - data_loader
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: models
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: data_loader
          type: data_loader
          config: default
          split: test
          args: default
        metrics:
          - name: Precision
            type: precision
            value: 0.8940149625935162
          - name: Recall
            type: recall
            value: 0.9168797953964194
          - name: F1
            type: f1
            value: 0.9053030303030304
          - name: Accuracy
            type: accuracy
            value: 0.9743718592964824

models

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

Loss: 0.1595
Precision: 0.8940
Recall: 0.9169
F1: 0.9053
Accuracy: 0.9744

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	2.5	100	0.1926	0.7730	0.8274	0.7993	0.9452
No log	5.0	200	0.1342	0.8285	0.8708	0.8491	0.9583
No log	7.5	300	0.1217	0.8758	0.9015	0.8885	0.9693
No log	10.0	400	0.1157	0.9082	0.9233	0.9157	0.9769
0.15	12.5	500	0.1310	0.9011	0.9092	0.9052	0.9744
0.15	15.0	600	0.1583	0.8682	0.9015	0.8846	0.9693
0.15	17.5	700	0.1628	0.8867	0.9105	0.8984	0.9724
0.15	20.0	800	0.1594	0.8945	0.9220	0.9081	0.9749
0.15	22.5	900	0.1579	0.8940	0.9169	0.9053	0.9744
0.0047	25.0	1000	0.1595	0.8940	0.9169	0.9053	0.9744

Framework versions

Transformers 4.40.0.dev0
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2