| | --- |
| | license: cc-by-nc-sa-4.0 |
| | base_model: microsoft/layoutlmv3-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: layoutlmv3-cord |
| | 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. --> |
| |
|
| | # layoutlmv3-cord |
| |
|
| | 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: 0.1589 |
| | - Precision: 0.9433 |
| | - Recall: 0.9521 |
| | - F1: 0.9477 |
| | - Accuracy: 0.9669 |
| |
|
| | ## 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: 5e-05 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - training_steps: 1000 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | No log | 0.5 | 100 | 0.6487 | 0.7825 | 0.8006 | 0.7914 | 0.8330 | |
| | | No log | 1.0 | 200 | 0.4266 | 0.8496 | 0.8686 | 0.8590 | 0.8925 | |
| | | No log | 1.5 | 300 | 0.2553 | 0.9008 | 0.9057 | 0.9033 | 0.9341 | |
| | | No log | 2.0 | 400 | 0.2496 | 0.8960 | 0.9057 | 0.9008 | 0.9295 | |
| | | 0.5667 | 2.5 | 500 | 0.2016 | 0.9274 | 0.9374 | 0.9324 | 0.9554 | |
| | | 0.5667 | 3.0 | 600 | 0.1806 | 0.9387 | 0.9467 | 0.9427 | 0.9609 | |
| | | 0.5667 | 3.5 | 700 | 0.1667 | 0.9424 | 0.9474 | 0.9449 | 0.9630 | |
| | | 0.5667 | 4.0 | 800 | 0.1735 | 0.9452 | 0.9467 | 0.9459 | 0.9639 | |
| | | 0.5667 | 4.5 | 900 | 0.1657 | 0.9456 | 0.9529 | 0.9492 | 0.9660 | |
| | | 0.1025 | 5.0 | 1000 | 0.1589 | 0.9433 | 0.9521 | 0.9477 | 0.9669 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.36.0 |
| | - Pytorch 2.0.0 |
| | - Datasets 2.16.1 |
| | - Tokenizers 0.15.0 |
| |
|
