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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: model-2024-06-06
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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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+ # model-2024-06-06
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5257
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+ - Precision: 0.7422
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+ - Recall: 0.7427
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+ - F1: 0.7424
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+ - Accuracy: 0.8617
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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 | 0.6 | 100 | 1.4725 | 0.2387 | 0.0987 | 0.1396 | 0.6316 |
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+ | No log | 1.19 | 200 | 0.9815 | 0.5362 | 0.434 | 0.4797 | 0.7585 |
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+ | No log | 1.79 | 300 | 0.7596 | 0.6422 | 0.5707 | 0.6043 | 0.8071 |
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+ | No log | 2.38 | 400 | 0.6719 | 0.6739 | 0.6433 | 0.6583 | 0.8240 |
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+ | 1.1397 | 2.98 | 500 | 0.5865 | 0.7118 | 0.7013 | 0.7065 | 0.8429 |
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+ | 1.1397 | 3.57 | 600 | 0.5910 | 0.7293 | 0.722 | 0.7256 | 0.8505 |
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+ | 1.1397 | 4.17 | 700 | 0.5456 | 0.7373 | 0.726 | 0.7316 | 0.8524 |
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+ | 1.1397 | 4.76 | 800 | 0.5343 | 0.7376 | 0.7327 | 0.7351 | 0.8557 |
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+ | 1.1397 | 5.36 | 900 | 0.5327 | 0.7283 | 0.7487 | 0.7383 | 0.8569 |
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+ | 0.4593 | 5.95 | 1000 | 0.5257 | 0.7422 | 0.7427 | 0.7424 | 0.8617 |
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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 2.3.0+cu121
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+ - Datasets 2.19.2
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+ - Tokenizers 0.13.3
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