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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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+ 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: LayoutLMv3_5_entities
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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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+ # LayoutLMv3_5_entities
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+
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+ This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1966
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+ - Precision: 0.8679
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+ - Recall: 0.8519
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+ - F1: 0.8598
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+ - Accuracy: 0.9772
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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: 2000
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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 | 2.56 | 100 | 0.1209 | 0.8602 | 0.7407 | 0.7960 | 0.9666 |
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+ | No log | 5.13 | 200 | 0.1267 | 0.8365 | 0.8056 | 0.8208 | 0.9710 |
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+ | No log | 7.69 | 300 | 0.1673 | 0.8830 | 0.7685 | 0.8218 | 0.9701 |
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+ | No log | 10.26 | 400 | 0.1428 | 0.8911 | 0.8333 | 0.8612 | 0.9745 |
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+ | 0.0687 | 12.82 | 500 | 0.1457 | 0.8636 | 0.8796 | 0.8716 | 0.9763 |
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+ | 0.0687 | 15.38 | 600 | 0.1854 | 0.9062 | 0.8056 | 0.8529 | 0.9754 |
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+ | 0.0687 | 17.95 | 700 | 0.1841 | 0.8835 | 0.8426 | 0.8626 | 0.9772 |
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+ | 0.0687 | 20.51 | 800 | 0.1728 | 0.8505 | 0.8426 | 0.8465 | 0.9754 |
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+ | 0.0687 | 23.08 | 900 | 0.1986 | 0.8505 | 0.8426 | 0.8465 | 0.9745 |
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+ | 0.0038 | 25.64 | 1000 | 0.2087 | 0.8558 | 0.8241 | 0.8396 | 0.9737 |
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+ | 0.0038 | 28.21 | 1100 | 0.1949 | 0.8545 | 0.8704 | 0.8624 | 0.9772 |
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+ | 0.0038 | 30.77 | 1200 | 0.1954 | 0.8532 | 0.8611 | 0.8571 | 0.9763 |
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+ | 0.0038 | 33.33 | 1300 | 0.1912 | 0.8624 | 0.8704 | 0.8664 | 0.9781 |
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+ | 0.0038 | 35.9 | 1400 | 0.1926 | 0.8611 | 0.8611 | 0.8611 | 0.9772 |
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+ | 0.0003 | 38.46 | 1500 | 0.1969 | 0.8692 | 0.8611 | 0.8651 | 0.9763 |
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+ | 0.0003 | 41.03 | 1600 | 0.1979 | 0.8611 | 0.8611 | 0.8611 | 0.9772 |
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+ | 0.0003 | 43.59 | 1700 | 0.1976 | 0.8598 | 0.8519 | 0.8558 | 0.9763 |
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+ | 0.0003 | 46.15 | 1800 | 0.1979 | 0.8598 | 0.8519 | 0.8558 | 0.9763 |
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+ | 0.0003 | 48.72 | 1900 | 0.1979 | 0.8679 | 0.8519 | 0.8598 | 0.9772 |
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+ | 0.0001 | 51.28 | 2000 | 0.1966 | 0.8679 | 0.8519 | 0.8598 | 0.9772 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.29.2
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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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