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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: layout3 |
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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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# layout3 |
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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: 0.6334 |
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- Precision: 0.8935 |
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- Recall: 0.9131 |
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- F1: 0.9032 |
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- Accuracy: 0.8586 |
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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 | 1.33 | 100 | 0.6874 | 0.7820 | 0.8073 | 0.7944 | 0.7841 | |
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| No log | 2.67 | 200 | 0.4485 | 0.8321 | 0.8838 | 0.8571 | 0.8474 | |
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| No log | 4.0 | 300 | 0.4403 | 0.8579 | 0.9086 | 0.8825 | 0.8414 | |
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| No log | 5.33 | 400 | 0.4593 | 0.8452 | 0.9056 | 0.8743 | 0.8341 | |
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| 0.5531 | 6.67 | 500 | 0.4881 | 0.8732 | 0.9170 | 0.8946 | 0.8575 | |
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| 0.5531 | 8.0 | 600 | 0.5332 | 0.8761 | 0.9101 | 0.8928 | 0.8547 | |
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| 0.5531 | 9.33 | 700 | 0.5910 | 0.8894 | 0.9106 | 0.8999 | 0.8517 | |
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| 0.5531 | 10.67 | 800 | 0.5914 | 0.8909 | 0.9131 | 0.9019 | 0.8557 | |
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| 0.5531 | 12.0 | 900 | 0.6127 | 0.9001 | 0.9180 | 0.9090 | 0.8614 | |
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| 0.1245 | 13.33 | 1000 | 0.6334 | 0.8935 | 0.9131 | 0.9032 | 0.8586 | |
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### Framework versions |
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- Transformers 4.32.0 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.17.1 |
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- Tokenizers 0.13.2 |
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