| | --- |
| | license: cc-by-nc-sa-4.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: LayoutLM_1 |
| | 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_1 |
| | |
| | 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: 0.4204 |
| | - Precision: 0.6552 |
| | - Recall: 0.7480 |
| | - F1: 0.6985 |
| | - Accuracy: 0.9071 |
| | |
| | ## 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 | 3.7 | 100 | 0.6185 | 0.0 | 0.0 | 0.0 | 0.8310 | |
| | | No log | 7.41 | 200 | 0.4585 | 0.6146 | 0.4646 | 0.5291 | 0.8839 | |
| | | No log | 11.11 | 300 | 0.4020 | 0.5870 | 0.6378 | 0.6113 | 0.8929 | |
| | | No log | 14.81 | 400 | 0.3775 | 0.6496 | 0.7008 | 0.6742 | 0.9006 | |
| | | 0.4776 | 18.52 | 500 | 0.3826 | 0.6268 | 0.7008 | 0.6617 | 0.9019 | |
| | | 0.4776 | 22.22 | 600 | 0.3864 | 0.6224 | 0.7008 | 0.6593 | 0.8981 | |
| | | 0.4776 | 25.93 | 700 | 0.4307 | 0.5759 | 0.7165 | 0.6386 | 0.8916 | |
| | | 0.4776 | 29.63 | 800 | 0.4205 | 0.6738 | 0.7480 | 0.7090 | 0.9123 | |
| | | 0.4776 | 33.33 | 900 | 0.4176 | 0.6552 | 0.7480 | 0.6985 | 0.9084 | |
| | | 0.0536 | 37.04 | 1000 | 0.4204 | 0.6552 | 0.7480 | 0.6985 | 0.9071 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.29.2 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.13.3 |
| | |
