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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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+ base_model: microsoft/layoutlmv3-base
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - doc_lay_net-small
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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-DocLayNet-test
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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: doc_lay_net-small
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+ type: doc_lay_net-small
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+ config: DocLayNet_2022.08_processed_on_2023.01
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+ split: test
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+ args: DocLayNet_2022.08_processed_on_2023.01
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.580814717477004
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+ - name: Recall
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+ type: recall
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+ value: 0.6415094339622641
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+ - name: F1
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+ type: f1
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+ value: 0.6096551724137931
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.867559907240402
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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-DocLayNet-test
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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 doc_lay_net-small dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5326
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+ - Precision: 0.5808
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+ - Recall: 0.6415
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+ - F1: 0.6097
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+ - Accuracy: 0.8676
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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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - training_steps: 1000
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+ - mixed_precision_training: Native AMP
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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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+ | 1.499 | 0.37 | 250 | 0.7771 | 0.2079 | 0.2848 | 0.2403 | 0.8189 |
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+ | 0.8163 | 0.73 | 500 | 0.5990 | 0.3611 | 0.5633 | 0.4400 | 0.8454 |
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+ | 0.5933 | 1.1 | 750 | 0.6424 | 0.5527 | 0.6139 | 0.5817 | 0.8182 |
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+ | 0.3731 | 1.46 | 1000 | 0.7426 | 0.5923 | 0.6804 | 0.6333 | 0.8282 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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+ {
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