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README.md
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---
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library_name: transformers
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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-ap7_1_ip
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results: []
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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-ap7_1_ip
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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: 0.0246
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- Precision: 0.7719
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- Recall: 0.8302
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- F1: 0.8
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- Accuracy: 0.9961
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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: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.5176 | 14.7059 | 250 | 0.0664 | 0.45 | 0.1698 | 0.2466 | 0.9881 |
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| 0.0288 | 29.4118 | 500 | 0.0354 | 0.6538 | 0.6415 | 0.6476 | 0.9930 |
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| 0.0143 | 44.1176 | 750 | 0.0269 | 0.7333 | 0.8302 | 0.7788 | 0.9956 |
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| 0.0098 | 58.8235 | 1000 | 0.0246 | 0.7719 | 0.8302 | 0.8 | 0.9961 |
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### Framework versions
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- Transformers 4.48.3
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- Pytorch 2.6.0+cu124
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- Datasets 3.4.1
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- Tokenizers 0.21.1
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