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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: LayoutLM_4
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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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+ # LayoutLM_4
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6673
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+ - Precision: 0.675
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+ - Recall: 0.3576
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+ - F1: 0.4675
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+ - Accuracy: 0.8559
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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-06
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+ - train_batch_size: 4
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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: 1500
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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 | 7.14 | 100 | 1.2248 | 0.0 | 0.0 | 0.0 | 0.7818 |
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+ | No log | 14.29 | 200 | 0.9800 | 0.0 | 0.0 | 0.0 | 0.7818 |
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+ | No log | 21.43 | 300 | 0.8988 | 0.0 | 0.0 | 0.0 | 0.7818 |
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+ | No log | 28.57 | 400 | 0.8416 | 0.0 | 0.0 | 0.0 | 0.7818 |
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+ | 1.0601 | 35.71 | 500 | 0.8025 | 0.0 | 0.0 | 0.0 | 0.7818 |
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+ | 1.0601 | 42.86 | 600 | 0.7719 | 0.0 | 0.0 | 0.0 | 0.7818 |
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+ | 1.0601 | 50.0 | 700 | 0.7428 | 0.75 | 0.0397 | 0.0755 | 0.7902 |
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+ | 1.0601 | 57.14 | 800 | 0.7225 | 0.5714 | 0.0530 | 0.0970 | 0.7972 |
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+ | 1.0601 | 64.29 | 900 | 0.7107 | 0.6923 | 0.1192 | 0.2034 | 0.8140 |
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+ | 0.6088 | 71.43 | 1000 | 0.6954 | 0.6444 | 0.1921 | 0.2959 | 0.8308 |
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+ | 0.6088 | 78.57 | 1100 | 0.6861 | 0.6727 | 0.2450 | 0.3592 | 0.8392 |
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+ | 0.6088 | 85.71 | 1200 | 0.6800 | 0.6719 | 0.2848 | 0.4 | 0.8462 |
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+ | 0.6088 | 92.86 | 1300 | 0.6694 | 0.6901 | 0.3245 | 0.4414 | 0.8517 |
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+ | 0.6088 | 100.0 | 1400 | 0.6684 | 0.675 | 0.3576 | 0.4675 | 0.8573 |
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+ | 0.5237 | 107.14 | 1500 | 0.6673 | 0.675 | 0.3576 | 0.4675 | 0.8559 |
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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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