---
library_name: transformers
license: mit
base_model: microsoft/table-transformer-structure-recognition-v1.1-all
tags:
- generated_from_trainer
model-index:
- name: detr_finetuned_cppe5
  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. -->

# detr_finetuned_cppe5

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 an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.3083
- eval_map: 0.0584
- eval_map_50: 0.1515
- eval_map_75: 0.0479
- eval_map_small: -1.0
- eval_map_medium: 0.007
- eval_map_large: 0.0646
- eval_mar_1: 0.0746
- eval_mar_10: 0.115
- eval_mar_100: 0.1545
- eval_mar_small: -1.0
- eval_mar_medium: 0.0439
- eval_mar_large: 0.1653
- eval_map_table: 0.2451
- eval_mar_100_table: 0.2882
- eval_map_table column: 0.0237
- eval_mar_100_table column: 0.1297
- eval_map_table column header: 0.0245
- eval_mar_100_table column header: 0.1224
- eval_map_table projected row header: 0.0003
- eval_mar_100_table projected row header: 0.0125
- eval_map_table row: 0.0254
- eval_mar_100_table row: 0.235
- eval_map_table spanning cell: 0.0311
- eval_mar_100_table spanning cell: 0.1393
- eval_runtime: 80.5383
- eval_samples_per_second: 0.633
- eval_steps_per_second: 0.087
- epoch: 1.0
- step: 22

## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: cosine
- num_epochs: 10

### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0