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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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+ datasets:
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+ - cord-layoutlmv3
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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-cord_100
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: cord-layoutlmv3
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+ type: cord-layoutlmv3
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+ config: cord
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+ split: train
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+ args: cord
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.9415247964470762
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+ - name: Recall
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+ type: recall
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+ value: 0.9520958083832335
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+ - name: F1
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+ type: f1
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+ value: 0.9467807964272422
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9575551782682513
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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-cord_100
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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 cord-layoutlmv3 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2246
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+ - Precision: 0.9415
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+ - Recall: 0.9521
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+ - F1: 0.9468
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+ - Accuracy: 0.9576
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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: 5
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+ - eval_batch_size: 5
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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: 2500
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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 | 1.56 | 250 | 1.0265 | 0.7630 | 0.8099 | 0.7858 | 0.8086 |
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+ | 1.4021 | 3.12 | 500 | 0.5804 | 0.8290 | 0.8638 | 0.8460 | 0.8718 |
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+ | 1.4021 | 4.69 | 750 | 0.3937 | 0.8882 | 0.9034 | 0.8957 | 0.9126 |
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+ | 0.4062 | 6.25 | 1000 | 0.3171 | 0.9137 | 0.9274 | 0.9205 | 0.9351 |
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+ | 0.4062 | 7.81 | 1250 | 0.2798 | 0.9332 | 0.9409 | 0.9370 | 0.9444 |
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+ | 0.2212 | 9.38 | 1500 | 0.2558 | 0.9277 | 0.9416 | 0.9346 | 0.9461 |
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+ | 0.2212 | 10.94 | 1750 | 0.2479 | 0.9335 | 0.9454 | 0.9394 | 0.9516 |
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+ | 0.1525 | 12.5 | 2000 | 0.2356 | 0.9444 | 0.9536 | 0.9490 | 0.9588 |
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+ | 0.1525 | 14.06 | 2250 | 0.2286 | 0.9365 | 0.9491 | 0.9428 | 0.9563 |
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+ | 0.1134 | 15.62 | 2500 | 0.2246 | 0.9415 | 0.9521 | 0.9468 | 0.9576 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.25.1
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+ - Pytorch 1.13.0+cu116
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+ - Datasets 2.8.0
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+ - Tokenizers 0.13.2