Instructions to use sh0KILLa/layoutlmv3-invoice-parser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sh0KILLa/layoutlmv3-invoice-parser with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sh0KILLa/layoutlmv3-invoice-parser")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("sh0KILLa/layoutlmv3-invoice-parser") model = AutoModelForTokenClassification.from_pretrained("sh0KILLa/layoutlmv3-invoice-parser", device_map="auto") - Notebooks
- Google Colab
- Kaggle
layoutlmv3-invoice-parser
This model is a fine-tuned version of microsoft/layoutlmv3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5061
- Precision: 0.8242
- Recall: 0.8936
- F1: 0.8575
- Accuracy: 0.8323
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.6703 | 1.0 | 38 | 0.7898 | 0.7234 | 0.8246 | 0.7707 | 0.7616 |
| 0.7077 | 2.0 | 76 | 0.6175 | 0.7751 | 0.8525 | 0.8120 | 0.7997 |
| 0.4946 | 3.0 | 114 | 0.5219 | 0.7856 | 0.8784 | 0.8294 | 0.8223 |
| 0.3819 | 4.0 | 152 | 0.5089 | 0.8109 | 0.8824 | 0.8451 | 0.8293 |
| 0.3178 | 5.0 | 190 | 0.5061 | 0.8242 | 0.8936 | 0.8575 | 0.8323 |
Framework versions
- Transformers 5.15.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Downloads last month
- 42
Model tree for sh0KILLa/layoutlmv3-invoice-parser
Base model
microsoft/layoutlmv3-base