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--- |
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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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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: layoutmlv3_sunday_sep3_v5 |
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results: [] |
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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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# layoutmlv3_sunday_sep3_v5 |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1630 |
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- Precision: 0.6867 |
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- Recall: 0.7308 |
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- F1: 0.7081 |
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- Accuracy: 0.9570 |
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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-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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: linear |
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- training_steps: 1000 |
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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 | 8.33 | 100 | 0.5150 | 0.5139 | 0.4744 | 0.4933 | 0.8460 | |
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| No log | 16.67 | 200 | 0.2462 | 0.5053 | 0.6154 | 0.5549 | 0.9387 | |
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| No log | 25.0 | 300 | 0.1973 | 0.6471 | 0.7051 | 0.6748 | 0.9536 | |
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| No log | 33.33 | 400 | 0.1617 | 0.6667 | 0.7179 | 0.6914 | 0.9520 | |
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| 0.3718 | 41.67 | 500 | 0.1630 | 0.6867 | 0.7308 | 0.7081 | 0.9570 | |
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| 0.3718 | 50.0 | 600 | 0.2247 | 0.5106 | 0.6154 | 0.5581 | 0.9073 | |
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| 0.3718 | 58.33 | 700 | 0.3364 | 0.5393 | 0.6154 | 0.5749 | 0.8907 | |
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| 0.3718 | 66.67 | 800 | 0.1783 | 0.5435 | 0.6410 | 0.5882 | 0.9454 | |
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| 0.3718 | 75.0 | 900 | 0.2255 | 0.5263 | 0.6410 | 0.5780 | 0.9305 | |
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| 0.0196 | 83.33 | 1000 | 0.2781 | 0.5158 | 0.6282 | 0.5665 | 0.9123 | |
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### Framework versions |
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- Transformers 4.33.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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