| | --- |
| | license: cc-by-nc-sa-4.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: LayoutLMv3_5_entities_7 |
| | 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_7 |
| | |
| | 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: 0.2592 |
| | - Precision: 0.8130 |
| | - Recall: 0.8850 |
| | - F1: 0.8475 |
| | - Accuracy: 0.9690 |
| | |
| | ## 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: 6e-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 | 0.1332 | 0.7154 | 0.8230 | 0.7654 | 0.9566 | |
| | | No log | 5.13 | 200 | 0.1432 | 0.7698 | 0.8584 | 0.8117 | 0.9646 | |
| | | No log | 7.69 | 300 | 0.1612 | 0.7805 | 0.8496 | 0.8136 | 0.9619 | |
| | | No log | 10.26 | 400 | 0.1885 | 0.8333 | 0.8407 | 0.8370 | 0.9655 | |
| | | 0.0796 | 12.82 | 500 | 0.2244 | 0.7724 | 0.8407 | 0.8051 | 0.9611 | |
| | | 0.0796 | 15.38 | 600 | 0.2407 | 0.8017 | 0.8584 | 0.8291 | 0.9655 | |
| | | 0.0796 | 17.95 | 700 | 0.2231 | 0.8167 | 0.8673 | 0.8412 | 0.9699 | |
| | | 0.0796 | 20.51 | 800 | 0.2435 | 0.7967 | 0.8673 | 0.8305 | 0.9655 | |
| | | 0.0796 | 23.08 | 900 | 0.2429 | 0.8167 | 0.8673 | 0.8412 | 0.9690 | |
| | | 0.0043 | 25.64 | 1000 | 0.2304 | 0.8684 | 0.8761 | 0.8722 | 0.9735 | |
| | | 0.0043 | 28.21 | 1100 | 0.2704 | 0.7823 | 0.8584 | 0.8186 | 0.9655 | |
| | | 0.0043 | 30.77 | 1200 | 0.2647 | 0.8033 | 0.8673 | 0.8340 | 0.9673 | |
| | | 0.0043 | 33.33 | 1300 | 0.2509 | 0.8115 | 0.8761 | 0.8426 | 0.9681 | |
| | | 0.0043 | 35.9 | 1400 | 0.2561 | 0.7967 | 0.8673 | 0.8305 | 0.9664 | |
| | | 0.0014 | 38.46 | 1500 | 0.2774 | 0.7823 | 0.8584 | 0.8186 | 0.9664 | |
| | | 0.0014 | 41.03 | 1600 | 0.2580 | 0.7951 | 0.8584 | 0.8255 | 0.9673 | |
| | | 0.0014 | 43.59 | 1700 | 0.2688 | 0.7937 | 0.8850 | 0.8368 | 0.9673 | |
| | | 0.0014 | 46.15 | 1800 | 0.2706 | 0.8 | 0.8850 | 0.8403 | 0.9681 | |
| | | 0.0014 | 48.72 | 1900 | 0.2608 | 0.8130 | 0.8850 | 0.8475 | 0.9690 | |
| | | 0.0008 | 51.28 | 2000 | 0.2592 | 0.8130 | 0.8850 | 0.8475 | 0.9690 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.29.2 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.13.3 |
| | |
