---
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