| --- |
| 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-finetuned-language-levels-v5-4000 |
| 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-finetuned-language-levels-v5-4000 |
|
|
| 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: 0.0913 |
| - Precision: 1.0 |
| - Recall: 1.0 |
| - F1: 1.0 |
| - Accuracy: 0.9824 |
|
|
| ## 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: 4000 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 0.2618 | 100 | 0.8184 | 0.9647 | 0.9630 | 0.9639 | 0.6971 | |
| | No log | 0.5236 | 200 | 0.6254 | 0.9743 | 0.9815 | 0.9779 | 0.7404 | |
| | No log | 0.7853 | 300 | 0.4760 | 0.9926 | 0.9944 | 0.9935 | 0.7981 | |
| | No log | 1.0471 | 400 | 0.3675 | 0.9798 | 0.9889 | 0.9843 | 0.8910 | |
| | 0.6763 | 1.3089 | 500 | 0.0913 | 1.0 | 1.0 | 1.0 | 0.9824 | |
| | 0.6763 | 1.5707 | 600 | 0.0375 | 1.0 | 1.0 | 1.0 | 0.9904 | |
| | 0.6763 | 1.8325 | 700 | 0.0149 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.6763 | 2.0942 | 800 | 0.0078 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.6763 | 2.3560 | 900 | 0.0047 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.037 | 2.6178 | 1000 | 0.0037 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.037 | 2.8796 | 1100 | 0.0030 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.037 | 3.1414 | 1200 | 0.0026 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.037 | 3.4031 | 1300 | 0.0022 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.037 | 3.6649 | 1400 | 0.0019 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0046 | 3.9267 | 1500 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0046 | 4.1885 | 1600 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0046 | 4.4503 | 1700 | 0.0014 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0046 | 4.7120 | 1800 | 0.0013 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0046 | 4.9738 | 1900 | 0.0012 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0025 | 5.2356 | 2000 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0025 | 5.4974 | 2100 | 0.0010 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0025 | 5.7592 | 2200 | 0.0010 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0025 | 6.0209 | 2300 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0025 | 6.2827 | 2400 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0017 | 6.5445 | 2500 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0017 | 6.8063 | 2600 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0017 | 7.0681 | 2700 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0017 | 7.3298 | 2800 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0017 | 7.5916 | 2900 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0013 | 7.8534 | 3000 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0013 | 8.1152 | 3100 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0013 | 8.3770 | 3200 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0013 | 8.6387 | 3300 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0013 | 8.9005 | 3400 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0011 | 9.1623 | 3500 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0011 | 9.4241 | 3600 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0011 | 9.6859 | 3700 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0011 | 9.9476 | 3800 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.0011 | 10.2094 | 3900 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | 0.001 | 10.4712 | 4000 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.43.3 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
|
|
