| --- |
| license: cc-by-nc-sa-4.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: LayoutLM_3 |
| 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. --> |
|
|
| # LayoutLM_3 |
| |
| This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7776 |
| - Precision: 0.0 |
| - Recall: 0.0 |
| - F1: 0.0 |
| - Accuracy: 0.7851 |
| |
| ## 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-06 |
| - 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 | 3.03 | 100 | 1.1551 | 0.0 | 0.0 | 0.0 | 0.7851 | |
| | No log | 6.06 | 200 | 0.9739 | 0.0 | 0.0 | 0.0 | 0.7851 | |
| | No log | 9.09 | 300 | 0.9131 | 0.0 | 0.0 | 0.0 | 0.7851 | |
| | No log | 12.12 | 400 | 0.8722 | 0.0 | 0.0 | 0.0 | 0.7851 | |
| | 1.0495 | 15.15 | 500 | 0.8338 | 0.0 | 0.0 | 0.0 | 0.7851 | |
| | 1.0495 | 18.18 | 600 | 0.8131 | 0.0 | 0.0 | 0.0 | 0.7851 | |
| | 1.0495 | 21.21 | 700 | 0.8001 | 0.0 | 0.0 | 0.0 | 0.7851 | |
| | 1.0495 | 24.24 | 800 | 0.7874 | 0.0 | 0.0 | 0.0 | 0.7851 | |
| | 1.0495 | 27.27 | 900 | 0.7797 | 0.0 | 0.0 | 0.0 | 0.7851 | |
| | 0.6789 | 30.3 | 1000 | 0.7776 | 0.0 | 0.0 | 0.0 | 0.7851 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.29.2 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.4 |
| - Tokenizers 0.13.3 |
| |
