metadata
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- invoice_layoutlmv3
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-intellectai
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: invoice_layoutlmv3
type: invoice_layoutlmv3
config: intellectai
split: validation
args: intellectai
metrics:
- name: Precision
type: precision
value: 0.7053571428571429
- name: Recall
type: recall
value: 0.8540540540540541
- name: F1
type: f1
value: 0.7726161369193154
- name: Accuracy
type: accuracy
value: 0.9624772313296903
layoutlmv3-finetuned-intellectai
This model is a fine-tuned version of microsoft/layoutlmv3-base on the invoice_layoutlmv3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3645
- Precision: 0.7054
- Recall: 0.8541
- F1: 0.7726
- Accuracy: 0.9625
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
- training_steps: 500
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 0.79 | 50 | 1.7979 | 0.0228 | 0.0541 | 0.0321 | 0.1410 |
No log | 1.59 | 100 | 1.2400 | 0.0863 | 0.4216 | 0.1433 | 0.2616 |
No log | 2.38 | 150 | 0.8691 | 0.1279 | 0.6919 | 0.2159 | 0.4495 |
No log | 3.17 | 200 | 0.6001 | 0.2323 | 0.8162 | 0.3617 | 0.7570 |
No log | 3.97 | 250 | 0.4709 | 0.4660 | 0.7784 | 0.5830 | 0.9093 |
No log | 4.76 | 300 | 0.3986 | 0.5977 | 0.8270 | 0.6939 | 0.9472 |
No log | 5.56 | 350 | 0.3762 | 0.5714 | 0.8216 | 0.6741 | 0.9454 |
No log | 6.35 | 400 | 0.3763 | 0.7048 | 0.8649 | 0.7767 | 0.9636 |
No log | 7.14 | 450 | 0.3696 | 0.6639 | 0.8541 | 0.7470 | 0.9570 |
0.71 | 7.94 | 500 | 0.3645 | 0.7054 | 0.8541 | 0.7726 | 0.9625 |
Framework versions
- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2