---
library_name: transformers
license: mit
base_model: microsoft/layoutlm-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- recall
- precision
model-index:
- name: Layouttest
  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. -->

# Layouttest

This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4410
- F1: 0.4615
- Recall: 0.3
- Precision: 1.0
- Pred Counts: {np.int64(5): 10}
- Actual Counts: {np.int64(5): 3, np.int64(6): 1, np.int64(3): 2, np.int64(18): 1, np.int64(0): 1, np.int64(15): 1, np.int64(25): 1}

## 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: 3e-05
- train_batch_size: 16
- 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: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.53.0.dev0
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1