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--- |
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license: cc-by-nc-sa-4.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: Output_LayoutLMv3_v7 |
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results: [] |
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datasets: |
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- Noureddinesa/LayoutLmv3_v1 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Output_LayoutLMv3_v7 |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1075 |
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- Precision: 0.7928 |
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- Recall: 0.8 |
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- F1: 0.7964 |
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- Accuracy: 0.9723 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-06 |
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- train_batch_size: 12 |
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- eval_batch_size: 12 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- training_steps: 2600 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 9.09 | 100 | 0.4138 | 0.0 | 0.0 | 0.0 | 0.8962 | |
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| No log | 18.18 | 200 | 0.2709 | 0.1667 | 0.0273 | 0.0469 | 0.9014 | |
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| No log | 27.27 | 300 | 0.2003 | 0.6234 | 0.4364 | 0.5134 | 0.9360 | |
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| No log | 36.36 | 400 | 0.1711 | 0.6496 | 0.6909 | 0.6696 | 0.9481 | |
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| 0.3384 | 45.45 | 500 | 0.1624 | 0.6667 | 0.7273 | 0.6957 | 0.9498 | |
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| 0.3384 | 54.55 | 600 | 0.1502 | 0.6803 | 0.7545 | 0.7155 | 0.9550 | |
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| 0.3384 | 63.64 | 700 | 0.1428 | 0.7227 | 0.7818 | 0.7511 | 0.9602 | |
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| 0.3384 | 72.73 | 800 | 0.1452 | 0.7049 | 0.7818 | 0.7414 | 0.9550 | |
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| 0.3384 | 81.82 | 900 | 0.1260 | 0.7544 | 0.7818 | 0.7679 | 0.9671 | |
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| 0.0995 | 90.91 | 1000 | 0.1254 | 0.7544 | 0.7818 | 0.7679 | 0.9671 | |
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| 0.0995 | 100.0 | 1100 | 0.1211 | 0.7863 | 0.8364 | 0.8106 | 0.9706 | |
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| 0.0995 | 109.09 | 1200 | 0.1093 | 0.7739 | 0.8091 | 0.7911 | 0.9706 | |
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| 0.0995 | 118.18 | 1300 | 0.1081 | 0.7946 | 0.8091 | 0.8018 | 0.9723 | |
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| 0.0995 | 127.27 | 1400 | 0.1108 | 0.7778 | 0.8273 | 0.8018 | 0.9723 | |
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| 0.0608 | 136.36 | 1500 | 0.1115 | 0.7627 | 0.8182 | 0.7895 | 0.9706 | |
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| 0.0608 | 145.45 | 1600 | 0.1034 | 0.8053 | 0.8273 | 0.8161 | 0.9740 | |
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| 0.0608 | 154.55 | 1700 | 0.1050 | 0.7895 | 0.8182 | 0.8036 | 0.9723 | |
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| 0.0608 | 163.64 | 1800 | 0.1093 | 0.7739 | 0.8091 | 0.7911 | 0.9706 | |
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| 0.0608 | 172.73 | 1900 | 0.1043 | 0.7965 | 0.8182 | 0.8072 | 0.9723 | |
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| 0.0443 | 181.82 | 2000 | 0.1048 | 0.8036 | 0.8182 | 0.8108 | 0.9758 | |
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| 0.0443 | 190.91 | 2100 | 0.1067 | 0.8036 | 0.8182 | 0.8108 | 0.9758 | |
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| 0.0443 | 200.0 | 2200 | 0.1069 | 0.8036 | 0.8182 | 0.8108 | 0.9740 | |
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| 0.0443 | 209.09 | 2300 | 0.1083 | 0.7928 | 0.8 | 0.7964 | 0.9723 | |
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| 0.0443 | 218.18 | 2400 | 0.1079 | 0.7928 | 0.8 | 0.7964 | 0.9723 | |
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| 0.0381 | 227.27 | 2500 | 0.1076 | 0.7928 | 0.8 | 0.7964 | 0.9723 | |
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| 0.0381 | 236.36 | 2600 | 0.1075 | 0.7928 | 0.8 | 0.7964 | 0.9723 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.13.3 |
