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---
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library_name: transformers
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license: mit
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base_model: microsoft/table-transformer-structure-recognition-v1.1-all
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tags:
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- generated_from_trainer
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datasets:
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- tr-fin_table-dataset-v4
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model-index:
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- name: table-transformer-structure-recognition-v1.1-all-finetuned-v4
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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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# table-transformer-structure-recognition-v1.1-all-finetuned-v4
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This model is a fine-tuned version of [microsoft/table-transformer-structure-recognition-v1.1-all](https://huggingface.co/microsoft/table-transformer-structure-recognition-v1.1-all) on the tr-fin_table-dataset-v4 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.5814
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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: 5e-06
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- train_batch_size: 4
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- eval_batch_size: 4
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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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- 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 |
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|:-------------:|:-----:|:----:|:---------------:|
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| 2.8161 | 12.5 | 50 | 1.8594 |
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| 2.1356 | 25.0 | 100 | 1.8244 |
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| 1.9666 | 37.5 | 150 | 1.7812 |
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| 2.686 | 50.0 | 200 | 1.7117 |
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| 1.8873 | 62.5 | 250 | 1.6662 |
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| 2.0797 | 75.0 | 300 | 1.6360 |
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| 2.2612 | 87.5 | 350 | 1.6419 |
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| 1.954 | 100.0 | 400 | 1.6110 |
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| 2.0358 | 112.5 | 450 | 1.6159 |
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| 1.9712 | 125.0 | 500 | 1.6164 |
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| 2.1658 | 137.5 | 550 | 1.6242 |
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| 2.7702 | 150.0 | 600 | 1.6097 |
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| 1.9429 | 162.5 | 650 | 1.6083 |
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| 1.947 | 175.0 | 700 | 1.5989 |
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| 2.0561 | 187.5 | 750 | 1.6029 |
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| 2.0323 | 200.0 | 800 | 1.5877 |
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| 2.0326 | 212.5 | 850 | 1.5870 |
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| 1.7113 | 225.0 | 900 | 1.5835 |
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| 1.6647 | 237.5 | 950 | 1.5811 |
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| 2.2978 | 250.0 | 1000 | 1.5814 |
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### Framework versions
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- Transformers 4.51.3
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- Pytorch 2.6.0+cu126
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- Datasets 3.5.0
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- Tokenizers 0.21.0
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