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End of training

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README.md ADDED
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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: primo_test
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+ results: []
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+ ---
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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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+
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+ # primo_test
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+
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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: 0.0105
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+ - Precision: 0.9744
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+ - Recall: 0.9902
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+ - F1: 0.9822
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+ - Accuracy: 0.9979
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 0.03 | 100 | 0.4646 | 0.8275 | 0.8656 | 0.8461 | 0.9306 |
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+ | No log | 0.06 | 200 | 0.0824 | 0.9614 | 0.9722 | 0.9667 | 0.9948 |
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+ | No log | 0.08 | 300 | 0.0363 | 0.9622 | 0.9859 | 0.9739 | 0.9951 |
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+ | No log | 0.11 | 400 | 0.0182 | 0.9756 | 0.9912 | 0.9833 | 0.9980 |
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+ | 0.3067 | 0.14 | 500 | 0.0217 | 0.9578 | 0.9813 | 0.9694 | 0.9960 |
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+ | 0.3067 | 0.17 | 600 | 0.0106 | 0.9913 | 0.9946 | 0.9929 | 0.9988 |
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+ | 0.3067 | 0.19 | 700 | 0.0121 | 0.9733 | 0.9894 | 0.9812 | 0.9977 |
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+ | 0.3067 | 0.22 | 800 | 0.0126 | 0.9699 | 0.9881 | 0.9789 | 0.9975 |
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+ | 0.3067 | 0.25 | 900 | 0.0098 | 0.9778 | 0.9915 | 0.9846 | 0.9982 |
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+ | 0.0105 | 0.28 | 1000 | 0.0105 | 0.9744 | 0.9902 | 0.9822 | 0.9979 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.1
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+ - Pytorch 2.1.1+cu121
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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