metadata
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- data_registros_layoutv3
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-registros_v2
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: data_registros_layoutv3
type: data_registros_layoutv3
config: default
split: test
args: default
metrics:
- name: Precision
type: precision
value: 0.860632183908046
- name: Recall
type: recall
value: 0.9374021909233177
- name: F1
type: f1
value: 0.8973782771535581
- name: Accuracy
type: accuracy
value: 0.9816688664026983
layoutlmv3-finetuned-registros_v2
This model is a fine-tuned version of microsoft/layoutlmv3-base on the data_registros_layoutv3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1473
- Precision: 0.8606
- Recall: 0.9374
- F1: 0.8974
- Accuracy: 0.9817
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: 5e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 10.87 | 250 | 0.4204 | 0.4257 | 0.4351 | 0.4303 | 0.9104 |
| 0.6077 | 21.74 | 500 | 0.2246 | 0.7957 | 0.8654 | 0.8291 | 0.9683 |
| 0.6077 | 32.61 | 750 | 0.1636 | 0.8438 | 0.9218 | 0.8811 | 0.9765 |
| 0.1638 | 43.48 | 1000 | 0.1473 | 0.8606 | 0.9374 | 0.8974 | 0.9817 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3