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: 1
- name: Recall
type: recall
value: 1
- name: F1
type: f1
value: 1
- name: Accuracy
type: accuracy
value: 1
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: 0.0013
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
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: 2000
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.144 | 5.0 | 500 | 0.0124 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
0.0081 | 10.0 | 1000 | 0.0042 | 0.9960 | 0.9980 | 0.9970 | 0.9996 |
0.0034 | 15.0 | 1500 | 0.0013 | 1.0 | 1.0 | 1.0 | 1.0 |
0.0023 | 20.0 | 2000 | 0.0018 | 0.9980 | 1.0 | 0.9990 | 0.9998 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1