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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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- accuracy |
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- f1 |
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model-index: |
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- name: layoutlmv3_document_classification |
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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_document_classification |
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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: 0.6852 |
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- Accuracy: 0.8480 |
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- F1: 0.8373 |
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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: 3e-05 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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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: 0.06 |
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- num_epochs: 10 |
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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 | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 4.1758 | 0.5 | 100 | 3.6479 | 0.1754 | 0.0743 | |
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| 3.1634 | 1.0 | 200 | 2.5074 | 0.4645 | 0.3598 | |
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| 2.2494 | 1.5 | 300 | 1.9309 | 0.5856 | 0.4950 | |
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| 1.8063 | 2.0 | 400 | 1.5119 | 0.6817 | 0.6152 | |
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| 1.458 | 2.5 | 500 | 1.2952 | 0.7126 | 0.6529 | |
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| 1.2453 | 3.0 | 600 | 1.1118 | 0.7728 | 0.7327 | |
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| 1.046 | 3.5 | 700 | 1.0126 | 0.7987 | 0.7681 | |
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| 0.966 | 4.0 | 800 | 0.9096 | 0.8154 | 0.7929 | |
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| 0.7941 | 4.5 | 900 | 0.8714 | 0.8179 | 0.7972 | |
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| 0.7796 | 5.0 | 1000 | 0.8019 | 0.8329 | 0.8126 | |
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| 0.6561 | 5.5 | 1100 | 0.7623 | 0.8421 | 0.8235 | |
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| 0.6419 | 6.0 | 1200 | 0.7399 | 0.8421 | 0.8262 | |
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| 0.5715 | 6.5 | 1300 | 0.7127 | 0.8480 | 0.8321 | |
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| 0.4991 | 7.0 | 1400 | 0.7502 | 0.8396 | 0.8257 | |
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| 0.4697 | 7.5 | 1500 | 0.7124 | 0.8429 | 0.8305 | |
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| 0.4618 | 8.0 | 1600 | 0.6976 | 0.8463 | 0.8330 | |
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| 0.4117 | 8.5 | 1700 | 0.6892 | 0.8546 | 0.8429 | |
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| 0.4274 | 9.0 | 1800 | 0.6915 | 0.8496 | 0.8390 | |
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| 0.383 | 9.5 | 1900 | 0.6830 | 0.8471 | 0.8349 | |
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| 0.3604 | 10.0 | 2000 | 0.6852 | 0.8480 | 0.8373 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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