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End of training

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: SCUT-DLVCLab/lilt-roberta-en-base
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - funsd-layoutlmv3
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+ model-index:
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+ - name: lilt-en-funsd
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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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+ # lilt-en-funsd
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+
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+ This model is a fine-tuned version of [SCUT-DLVCLab/lilt-roberta-en-base](https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base) on the funsd-layoutlmv3 dataset.
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+ It achieves the following results on the evaluation set:
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+ - eval_loss: 2.0243
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+ - eval_ANSWER: {'precision': 0.039603960396039604, 'recall': 0.2692778457772338, 'f1': 0.06905210295040803, 'number': 817}
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+ - eval_HEADER: {'precision': 0.0024509803921568627, 'recall': 0.01680672268907563, 'f1': 0.00427807486631016, 'number': 119}
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+ - eval_QUESTION: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1077}
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+ - eval_overall_precision: 0.0310
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+ - eval_overall_recall: 0.1103
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+ - eval_overall_f1: 0.0484
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+ - eval_overall_accuracy: 0.1168
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+ - eval_runtime: 4.1649
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+ - eval_samples_per_second: 12.005
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+ - eval_steps_per_second: 1.681
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+ - step: 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: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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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+ ### Framework versions
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+
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+ - Transformers 4.34.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
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