|
--- |
|
license: cc-by-nc-sa-4.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- cord-layoutlmv3 |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: layoutlmv3-finetuned-cord_500 |
|
results: |
|
- task: |
|
name: Token Classification |
|
type: token-classification |
|
dataset: |
|
name: cord-layoutlmv3 |
|
type: cord-layoutlmv3 |
|
config: cord |
|
split: train |
|
args: cord |
|
metrics: |
|
- name: Precision |
|
type: precision |
|
value: 0.9509293680297398 |
|
- name: Recall |
|
type: recall |
|
value: 0.9573353293413174 |
|
- name: F1 |
|
type: f1 |
|
value: 0.9541215964192465 |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9609507640067911 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# layoutlmv3-finetuned-cord_500 |
|
|
|
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the cord-layoutlmv3 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2339 |
|
- Precision: 0.9509 |
|
- Recall: 0.9573 |
|
- F1: 0.9541 |
|
- Accuracy: 0.9610 |
|
|
|
## 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: 5 |
|
- eval_batch_size: 5 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- training_steps: 4000 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| No log | 2.5 | 250 | 0.9950 | 0.7114 | 0.7784 | 0.7434 | 0.7903 | |
|
| 1.3831 | 5.0 | 500 | 0.5152 | 0.8483 | 0.8787 | 0.8632 | 0.8816 | |
|
| 1.3831 | 7.5 | 750 | 0.3683 | 0.9013 | 0.9154 | 0.9083 | 0.9240 | |
|
| 0.3551 | 10.0 | 1000 | 0.3051 | 0.9201 | 0.9304 | 0.9252 | 0.9363 | |
|
| 0.3551 | 12.5 | 1250 | 0.2636 | 0.9375 | 0.9424 | 0.9399 | 0.9457 | |
|
| 0.1562 | 15.0 | 1500 | 0.2498 | 0.9385 | 0.9476 | 0.9430 | 0.9508 | |
|
| 0.1562 | 17.5 | 1750 | 0.2380 | 0.9414 | 0.9499 | 0.9456 | 0.9559 | |
|
| 0.0863 | 20.0 | 2000 | 0.2355 | 0.9400 | 0.9491 | 0.9445 | 0.9542 | |
|
| 0.0863 | 22.5 | 2250 | 0.2268 | 0.9451 | 0.9536 | 0.9493 | 0.9601 | |
|
| 0.0512 | 25.0 | 2500 | 0.2277 | 0.9429 | 0.9513 | 0.9471 | 0.9588 | |
|
| 0.0512 | 27.5 | 2750 | 0.2315 | 0.9473 | 0.9551 | 0.9512 | 0.9593 | |
|
| 0.0358 | 30.0 | 3000 | 0.2294 | 0.9509 | 0.9573 | 0.9541 | 0.9605 | |
|
| 0.0358 | 32.5 | 3250 | 0.2330 | 0.9458 | 0.9543 | 0.9501 | 0.9593 | |
|
| 0.028 | 35.0 | 3500 | 0.2374 | 0.9487 | 0.9558 | 0.9523 | 0.9597 | |
|
| 0.028 | 37.5 | 3750 | 0.2374 | 0.9501 | 0.9558 | 0.9530 | 0.9593 | |
|
| 0.0244 | 40.0 | 4000 | 0.2339 | 0.9509 | 0.9573 | 0.9541 | 0.9610 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.21.2 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|
