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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: layoutlmv3-finetuned-language-levels-v2
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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-finetuned-language-levels-v2
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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: 0.0006
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+ - Precision: 1.0
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+ - Recall: 1.0
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+ - F1: 1.0
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+ - Accuracy: 1.0
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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 | 0.0320 | 100 | 0.0058 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 0.0640 | 200 | 0.0022 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 0.0959 | 300 | 0.0013 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 0.1279 | 400 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0705 | 0.1599 | 500 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0705 | 0.1919 | 600 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0705 | 0.2239 | 700 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0705 | 0.2558 | 800 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0705 | 0.2878 | 900 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0006 | 0.3198 | 1000 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0006 | 0.3518 | 1100 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0006 | 0.3838 | 1200 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0006 | 0.4157 | 1300 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0006 | 0.4477 | 1400 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0003 | 0.4797 | 1500 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0003 | 0.5117 | 1600 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0003 | 0.5437 | 1700 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0003 | 0.5756 | 1800 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0003 | 0.6076 | 1900 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0002 | 0.6396 | 2000 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.43.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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