README.md

metadata

library_name: transformers
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
  - generated_from_trainer
datasets:
  - doc_lay_net-small
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: Layoutlmv3-finetuned-DocLayNet-test-10-21
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: doc_lay_net-small
          type: doc_lay_net-small
          config: DocLayNet_2022.08_processed_on_2023.01
          split: test
          args: DocLayNet_2022.08_processed_on_2023.01
        metrics:
          - name: Precision
            type: precision
            value: 0.37793301092602544
          - name: Recall
            type: recall
            value: 0.37793301092602544
          - name: F1
            type: f1
            value: 0.37793301092602544
          - name: Accuracy
            type: accuracy
            value: 0.37793301092602544

Layoutlmv3-finetuned-DocLayNet-test-10-21

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

• Loss: 2.0791
• Precision: 0.3779
• Recall: 0.3779
• F1: 0.3779
• Accuracy: 0.3779

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
• lr_scheduler_warmup_ratio: 0.1
• training_steps: 10
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.45.2
• Pytorch 2.5.0+cu124
• Datasets 3.0.1
• Tokenizers 0.20.1