| | --- |
| | license: cc-by-nc-sa-4.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: LayoutLMv3_5_entities_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. --> |
| |
|
| | # LayoutLMv3_5_entities_3 |
| | |
| | This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2107 |
| | - Precision: 0.8835 |
| | - Recall: 0.8426 |
| | - F1: 0.8626 |
| | - Accuracy: 0.9729 |
| | |
| | ## 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-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: 2000 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | No log | 2.56 | 100 | 0.1391 | 0.78 | 0.7222 | 0.7500 | 0.9575 | |
| | | No log | 5.13 | 200 | 0.1103 | 0.8725 | 0.8241 | 0.8476 | 0.9720 | |
| | | No log | 7.69 | 300 | 0.1415 | 0.8922 | 0.8426 | 0.8667 | 0.9739 | |
| | | No log | 10.26 | 400 | 0.1649 | 0.8378 | 0.8611 | 0.8493 | 0.9710 | |
| | | 0.0838 | 12.82 | 500 | 0.1545 | 0.8713 | 0.8148 | 0.8421 | 0.9729 | |
| | | 0.0838 | 15.38 | 600 | 0.1396 | 0.8545 | 0.8704 | 0.8624 | 0.9749 | |
| | | 0.0838 | 17.95 | 700 | 0.1523 | 0.8942 | 0.8611 | 0.8774 | 0.9768 | |
| | | 0.0838 | 20.51 | 800 | 0.1718 | 0.8519 | 0.8519 | 0.8519 | 0.9710 | |
| | | 0.0838 | 23.08 | 900 | 0.2242 | 0.87 | 0.8056 | 0.8365 | 0.9700 | |
| | | 0.0044 | 25.64 | 1000 | 0.2165 | 0.88 | 0.8148 | 0.8462 | 0.9710 | |
| | | 0.0044 | 28.21 | 1100 | 0.2235 | 0.8866 | 0.7963 | 0.8390 | 0.9681 | |
| | | 0.0044 | 30.77 | 1200 | 0.2174 | 0.9 | 0.8333 | 0.8654 | 0.9739 | |
| | | 0.0044 | 33.33 | 1300 | 0.1991 | 0.8692 | 0.8611 | 0.8651 | 0.9729 | |
| | | 0.0044 | 35.9 | 1400 | 0.1986 | 0.8762 | 0.8519 | 0.8638 | 0.9739 | |
| | | 0.0015 | 38.46 | 1500 | 0.2061 | 0.8713 | 0.8148 | 0.8421 | 0.9700 | |
| | | 0.0015 | 41.03 | 1600 | 0.1970 | 0.8641 | 0.8241 | 0.8436 | 0.9710 | |
| | | 0.0015 | 43.59 | 1700 | 0.2127 | 0.8614 | 0.8056 | 0.8325 | 0.9700 | |
| | | 0.0015 | 46.15 | 1800 | 0.2070 | 0.875 | 0.8426 | 0.8585 | 0.9729 | |
| | | 0.0015 | 48.72 | 1900 | 0.2097 | 0.8835 | 0.8426 | 0.8626 | 0.9729 | |
| | | 0.0008 | 51.28 | 2000 | 0.2107 | 0.8835 | 0.8426 | 0.8626 | 0.9729 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.29.2 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.13.3 |
| | |
