LayoutLMv3-Fine-Tuning-Invoice Model
Model description
LayoutLMv3-Fine-Tuning-Invoice Model is a fine-tuned version of microsoft/layoutlmv3-base on the invoice dataset. For the fine-tuning, We used [Invoice Dataset] that includes 12 labels ('Other', 'ABN', 'BILLER', 'BILLER_ADDRESS', 'BILLER_POST_CODE', 'DUE_DATE', 'GST', 'INVOICE_DATE', 'INVOICE_NUMBER', 'SUBTOTAL', 'TOTAL', 'BILLER_ADDRESS').
This model is a fine-tuned version of microsoft/layoutlmv3-base on the invoice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.005334
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1.5e-05
- train_batch_size: 2
- eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 1000
Training results
Training Loss | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|
No log | 100 | 0.070030 | 0.972000 | 0.985801 | 0.978852 | 0.997051 |
No log | 200 | 0.017637 | 0.972000 | 0.985801 | 0.978852 | 0.997051 |
No log | 300 | 0.015573 | 0.972000 | 0.985801 | 0.978852 | 0.997051 |
No log | 400 | 0.011000 | 0.973737 | 0.977688 | 0.978852 | 0.996419 |
0.110800 | 500 | 0.005334 | 1.0 | 1.0 | 1.0 | 1.0 |
0.110800 | 600 | 0.002994 | 1.0 | 1.0 | 1.0 | 1.0 |
0.110800 | 700 | 0.002330 | 1.0 | 1.0 | 1.0 | 1.0 |
0.110800 | 800 | 0.002188 | 1.0 | 1.0 | 1.0 | 1.0 |
0.110800 | 900 | 0.002105 | 1.0 | 1.0 | 1.0 | 1.0 |
0.004900 | 1000 | 0.002111 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.20.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1