---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: LayoutLM_1
  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. -->

# LayoutLM_1

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4204
- Precision: 0.6552
- Recall: 0.7480
- F1: 0.6985
- Accuracy: 0.9071

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 3.7   | 100  | 0.6185          | 0.0       | 0.0    | 0.0    | 0.8310   |
| No log        | 7.41  | 200  | 0.4585          | 0.6146    | 0.4646 | 0.5291 | 0.8839   |
| No log        | 11.11 | 300  | 0.4020          | 0.5870    | 0.6378 | 0.6113 | 0.8929   |
| No log        | 14.81 | 400  | 0.3775          | 0.6496    | 0.7008 | 0.6742 | 0.9006   |
| 0.4776        | 18.52 | 500  | 0.3826          | 0.6268    | 0.7008 | 0.6617 | 0.9019   |
| 0.4776        | 22.22 | 600  | 0.3864          | 0.6224    | 0.7008 | 0.6593 | 0.8981   |
| 0.4776        | 25.93 | 700  | 0.4307          | 0.5759    | 0.7165 | 0.6386 | 0.8916   |
| 0.4776        | 29.63 | 800  | 0.4205          | 0.6738    | 0.7480 | 0.7090 | 0.9123   |
| 0.4776        | 33.33 | 900  | 0.4176          | 0.6552    | 0.7480 | 0.6985 | 0.9084   |
| 0.0536        | 37.04 | 1000 | 0.4204          | 0.6552    | 0.7480 | 0.6985 | 0.9071   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3