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--- |
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library_name: transformers |
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license: cc-by-nc-sa-4.0 |
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base_model: microsoft/layoutlmv3-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- layoutlmv3 |
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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: layoutlm-CC-7 |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: layoutlmv3 |
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type: layoutlmv3 |
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config: FormsDataset |
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split: test |
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args: FormsDataset |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.12529002320185614 |
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- name: Recall |
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type: recall |
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value: 0.20224719101123595 |
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- name: F1 |
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type: f1 |
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value: 0.15472779369627507 |
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- name: Accuracy |
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type: accuracy |
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value: 0.19654427645788336 |
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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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# layoutlm-CC-7 |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the layoutlmv3 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.1612 |
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- Precision: 0.1253 |
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- Recall: 0.2022 |
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- F1: 0.1547 |
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- Accuracy: 0.1965 |
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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: 3e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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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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| 4.8141 | 1.0 | 1 | 4.7205 | 0.0921 | 0.1311 | 0.1082 | 0.0821 | |
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| 4.7028 | 2.0 | 2 | 4.6365 | 0.1414 | 0.2022 | 0.1664 | 0.1425 | |
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| 4.6011 | 3.0 | 3 | 4.5617 | 0.1230 | 0.2022 | 0.1530 | 0.1274 | |
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| 4.5126 | 4.0 | 4 | 4.4931 | 0.1174 | 0.2022 | 0.1486 | 0.1231 | |
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| 4.4376 | 5.0 | 5 | 4.4390 | 0.1166 | 0.2022 | 0.1479 | 0.1166 | |
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| 4.3778 | 6.0 | 6 | 4.3926 | 0.1166 | 0.2022 | 0.1479 | 0.1188 | |
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| 4.3224 | 7.0 | 7 | 4.3454 | 0.1166 | 0.2022 | 0.1479 | 0.1210 | |
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| 4.2658 | 8.0 | 8 | 4.3058 | 0.1166 | 0.2022 | 0.1479 | 0.1253 | |
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| 4.2182 | 9.0 | 9 | 4.2708 | 0.1179 | 0.2022 | 0.1490 | 0.1425 | |
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| 4.1796 | 10.0 | 10 | 4.2415 | 0.1208 | 0.2022 | 0.1513 | 0.1641 | |
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| 4.1423 | 11.0 | 11 | 4.2165 | 0.1222 | 0.2022 | 0.1523 | 0.1728 | |
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| 4.1197 | 12.0 | 12 | 4.1951 | 0.1230 | 0.2022 | 0.1530 | 0.1793 | |
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| 4.0976 | 13.0 | 13 | 4.1782 | 0.1241 | 0.2022 | 0.1538 | 0.1922 | |
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| 4.0801 | 14.0 | 14 | 4.1669 | 0.1253 | 0.2022 | 0.1547 | 0.1965 | |
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| 4.0627 | 15.0 | 15 | 4.1612 | 0.1253 | 0.2022 | 0.1547 | 0.1965 | |
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### Framework versions |
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- Transformers 4.47.0.dev0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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