|
--- |
|
license: cc-by-nc-sa-4.0 |
|
base_model: microsoft/layoutlmv3-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: layoutmlv3_thursday_sep7_v5 |
|
results: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# layoutmlv3_thursday_sep7_v5 |
|
|
|
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1416 |
|
- Precision: 0.5517 |
|
- Recall: 0.9412 |
|
- F1: 0.6957 |
|
- Accuracy: 0.9822 |
|
|
|
## 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: 1000 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| No log | 8.33 | 100 | 0.3243 | 0.5556 | 0.8824 | 0.6818 | 0.9485 | |
|
| No log | 16.67 | 200 | 0.1584 | 0.6087 | 0.8235 | 0.7 | 0.9734 | |
|
| No log | 25.0 | 300 | 0.1682 | 0.5517 | 0.9412 | 0.6957 | 0.9769 | |
|
| No log | 33.33 | 400 | 0.1773 | 0.4545 | 0.8824 | 0.6 | 0.9734 | |
|
| 0.2633 | 41.67 | 500 | 0.1631 | 0.4375 | 0.8235 | 0.5714 | 0.9751 | |
|
| 0.2633 | 50.0 | 600 | 0.1526 | 0.5517 | 0.9412 | 0.6957 | 0.9769 | |
|
| 0.2633 | 58.33 | 700 | 0.1430 | 0.5517 | 0.9412 | 0.6957 | 0.9840 | |
|
| 0.2633 | 66.67 | 800 | 0.1497 | 0.5517 | 0.9412 | 0.6957 | 0.9822 | |
|
| 0.2633 | 75.0 | 900 | 0.1418 | 0.5517 | 0.9412 | 0.6957 | 0.9805 | |
|
| 0.0111 | 83.33 | 1000 | 0.1416 | 0.5517 | 0.9412 | 0.6957 | 0.9822 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.0.dev0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.13.3 |
|
|
