metadata
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
datasets:
- generated
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-invoice
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: generated
type: generated
config: sroie
split: test
args: sroie
metrics:
- name: Precision
type: precision
value: 0.9698795180722891
- name: Recall
type: recall
value: 0.9797160243407708
- name: F1
type: f1
value: 0.9747729566094854
- name: Accuracy
type: accuracy
value: 0.9964187908152518
layoutlmv3-finetuned-invoice
This model is a fine-tuned version of microsoft/layoutlmv3-base on the generated dataset. It achieves the following results on the evaluation set:
- Loss: 0.0826
- Precision: 0.9699
- Recall: 0.9797
- F1: 0.9748
- Accuracy: 0.9964
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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 200
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 100 | 0.1528 | 0.9478 | 0.9574 | 0.9526 | 0.9941 |
| No log | 2.0 | 200 | 0.0826 | 0.9699 | 0.9797 | 0.9748 | 0.9964 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1