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---
library_name: transformers
license: mit
base_model: microsoft/table-transformer-structure-recognition-v1.1-all
tags:
- generated_from_trainer
datasets:
- tr-fin_table-dataset-v4
model-index:
- name: table-transformer-structure-recognition-v1.1-all-finetuned-v4
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# table-transformer-structure-recognition-v1.1-all-finetuned-v4
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.
It achieves the following results on the evaluation set:
- Loss: 1.5814
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.8161 | 12.5 | 50 | 1.8594 |
| 2.1356 | 25.0 | 100 | 1.8244 |
| 1.9666 | 37.5 | 150 | 1.7812 |
| 2.686 | 50.0 | 200 | 1.7117 |
| 1.8873 | 62.5 | 250 | 1.6662 |
| 2.0797 | 75.0 | 300 | 1.6360 |
| 2.2612 | 87.5 | 350 | 1.6419 |
| 1.954 | 100.0 | 400 | 1.6110 |
| 2.0358 | 112.5 | 450 | 1.6159 |
| 1.9712 | 125.0 | 500 | 1.6164 |
| 2.1658 | 137.5 | 550 | 1.6242 |
| 2.7702 | 150.0 | 600 | 1.6097 |
| 1.9429 | 162.5 | 650 | 1.6083 |
| 1.947 | 175.0 | 700 | 1.5989 |
| 2.0561 | 187.5 | 750 | 1.6029 |
| 2.0323 | 200.0 | 800 | 1.5877 |
| 2.0326 | 212.5 | 850 | 1.5870 |
| 1.7113 | 225.0 | 900 | 1.5835 |
| 1.6647 | 237.5 | 950 | 1.5811 |
| 2.2978 | 250.0 | 1000 | 1.5814 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.0
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