| | --- |
| | license: cc-by-nc-sa-4.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: LayoutLMv3_97_2 |
| | 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_97_2 |
| |
|
| | 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: 0.5892 |
| | - Precision: 0.8315 |
| | - Recall: 0.7721 |
| | - F1: 0.8007 |
| | - Accuracy: 0.9122 |
| |
|
| | ## 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: 2000 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | No log | 2.56 | 100 | 0.4807 | 0.6058 | 0.4966 | 0.5458 | 0.8297 | |
| | | No log | 5.13 | 200 | 0.3940 | 0.7553 | 0.6088 | 0.6742 | 0.8771 | |
| | | No log | 7.69 | 300 | 0.3804 | 0.7438 | 0.7109 | 0.7270 | 0.9008 | |
| | | No log | 10.26 | 400 | 0.3900 | 0.8185 | 0.8129 | 0.8157 | 0.9096 | |
| | | 0.2035 | 12.82 | 500 | 0.4102 | 0.8255 | 0.7721 | 0.7979 | 0.9087 | |
| | | 0.2035 | 15.38 | 600 | 0.4077 | 0.8095 | 0.8095 | 0.8095 | 0.9148 | |
| | | 0.2035 | 17.95 | 700 | 0.4915 | 0.7867 | 0.7653 | 0.7759 | 0.8982 | |
| | | 0.2035 | 20.51 | 800 | 0.4861 | 0.8269 | 0.7959 | 0.8111 | 0.9131 | |
| | | 0.2035 | 23.08 | 900 | 0.5051 | 0.7818 | 0.7313 | 0.7557 | 0.9052 | |
| | | 0.0117 | 25.64 | 1000 | 0.5404 | 0.8303 | 0.7653 | 0.7965 | 0.9069 | |
| | | 0.0117 | 28.21 | 1100 | 0.6110 | 0.8492 | 0.7279 | 0.7839 | 0.9061 | |
| | | 0.0117 | 30.77 | 1200 | 0.5379 | 0.8014 | 0.7823 | 0.7917 | 0.9096 | |
| | | 0.0117 | 33.33 | 1300 | 0.5343 | 0.8057 | 0.7755 | 0.7903 | 0.9131 | |
| | | 0.0117 | 35.9 | 1400 | 0.5590 | 0.8333 | 0.7653 | 0.7979 | 0.9140 | |
| | | 0.0013 | 38.46 | 1500 | 0.6296 | 0.8488 | 0.7449 | 0.7935 | 0.9122 | |
| | | 0.0013 | 41.03 | 1600 | 0.6089 | 0.8421 | 0.7619 | 0.8 | 0.9122 | |
| | | 0.0013 | 43.59 | 1700 | 0.5869 | 0.8291 | 0.7755 | 0.8014 | 0.9140 | |
| | | 0.0013 | 46.15 | 1800 | 0.5847 | 0.8291 | 0.7755 | 0.8014 | 0.9140 | |
| | | 0.0013 | 48.72 | 1900 | 0.5881 | 0.8285 | 0.7721 | 0.7993 | 0.9131 | |
| | | 0.0004 | 51.28 | 2000 | 0.5892 | 0.8315 | 0.7721 | 0.8007 | 0.9122 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.29.2 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.13.3 |
| |
|
