metadata
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
datasets:
- doc_lay_net-small
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Layoutlmv3-finetuned-DocLayNet-test
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: doc_lay_net-small
type: doc_lay_net-small
config: DocLayNet_2022.08_processed_on_2023.01
split: test
args: DocLayNet_2022.08_processed_on_2023.01
metrics:
- name: Precision
type: precision
value: 0.5207226354941552
- name: Recall
type: recall
value: 0.7111756168359942
- name: F1
type: f1
value: 0.6012269938650306
- name: Accuracy
type: accuracy
value: 0.842051017778923
Layoutlmv3-finetuned-DocLayNet-test
This model is a fine-tuned version of microsoft/layoutlmv3-base on the doc_lay_net-small dataset. It achieves the following results on the evaluation set:
- Loss: 0.5038
- Precision: 0.5207
- Recall: 0.7112
- F1: 0.6012
- Accuracy: 0.8421
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
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.5092 | 0.37 | 250 | 0.8072 | 0.1922 | 0.2342 | 0.2111 | 0.8227 |
| 0.8608 | 0.73 | 500 | 0.6402 | 0.3963 | 0.6108 | 0.4807 | 0.8596 |
| 0.6463 | 1.1 | 750 | 0.8042 | 0.5702 | 0.6297 | 0.5985 | 0.8080 |
| 0.4495 | 1.46 | 1000 | 0.8439 | 0.5353 | 0.6234 | 0.5760 | 0.8033 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3