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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: test
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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: 0.4115296803652968
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- name: Recall
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type: recall
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value: 0.5396706586826348
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- name: F1
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type: f1
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value: 0.46696891191709844
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- name: Accuracy
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type: accuracy
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value: 0.4350594227504245
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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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# layoutlmv3-finetuned-cord_100
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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: 2.5624
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- Precision: 0.4115
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- Recall: 0.5397
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- F1: 0.4670
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- Accuracy: 0.4351
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 100
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 0.06 | 10 | 3.8065 | 0.1637 | 0.2582 | 0.2003 | 0.2585 |
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| No log | 0.12 | 20 | 3.4787 | 0.4661 | 0.3862 | 0.4224 | 0.3353 |
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| No log | 0.19 | 30 | 3.2587 | 0.4332 | 0.4731 | 0.4522 | 0.3667 |
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| No log | 0.25 | 40 | 3.0615 | 0.4144 | 0.4873 | 0.4479 | 0.3846 |
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| No log | 0.31 | 50 | 2.9052 | 0.3993 | 0.5090 | 0.4475 | 0.4024 |
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| No log | 0.38 | 60 | 2.7819 | 0.3876 | 0.5165 | 0.4429 | 0.4143 |
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| No log | 0.44 | 70 | 2.6853 | 0.3891 | 0.5202 | 0.4452 | 0.4164 |
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| No log | 0.5 | 80 | 2.6245 | 0.3942 | 0.5269 | 0.4510 | 0.4236 |
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| No log | 0.56 | 90 | 2.5777 | 0.4056 | 0.5352 | 0.4614 | 0.4312 |
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| No log | 0.62 | 100 | 2.5624 | 0.4115 | 0.5397 | 0.4670 | 0.4351 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.1+cpu
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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