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: 0.010438413361169102
- name: Recall
type: recall
value: 0.02028397565922921
- name: F1
type: f1
value: 0.013783597518952447
- name: Accuracy
type: accuracy
value: 0.6785338108278913
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: 2.1320
- Precision: 0.0104
- Recall: 0.0203
- F1: 0.0138
- Accuracy: 0.6785
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 0.01 | 1 | 2.3858 | 0.0114 | 0.0649 | 0.0194 | 0.1904 |
| No log | 0.02 | 2 | 2.2795 | 0.0108 | 0.0527 | 0.0180 | 0.3240 |
| No log | 0.03 | 3 | 2.2072 | 0.0131 | 0.0446 | 0.0203 | 0.5155 |
| No log | 0.04 | 4 | 2.1575 | 0.0103 | 0.0243 | 0.0145 | 0.6345 |
| No log | 0.05 | 5 | 2.1320 | 0.0104 | 0.0203 | 0.0138 | 0.6785 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1