---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: LayoutLMv3_5_entities_7
  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. -->

# LayoutLMv3_5_entities_7

This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2592
- Precision: 0.8130
- Recall: 0.8850
- F1: 0.8475
- Accuracy: 0.9690

## 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: 6e-06
- 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: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 2.56  | 100  | 0.1332          | 0.7154    | 0.8230 | 0.7654 | 0.9566   |
| No log        | 5.13  | 200  | 0.1432          | 0.7698    | 0.8584 | 0.8117 | 0.9646   |
| No log        | 7.69  | 300  | 0.1612          | 0.7805    | 0.8496 | 0.8136 | 0.9619   |
| No log        | 10.26 | 400  | 0.1885          | 0.8333    | 0.8407 | 0.8370 | 0.9655   |
| 0.0796        | 12.82 | 500  | 0.2244          | 0.7724    | 0.8407 | 0.8051 | 0.9611   |
| 0.0796        | 15.38 | 600  | 0.2407          | 0.8017    | 0.8584 | 0.8291 | 0.9655   |
| 0.0796        | 17.95 | 700  | 0.2231          | 0.8167    | 0.8673 | 0.8412 | 0.9699   |
| 0.0796        | 20.51 | 800  | 0.2435          | 0.7967    | 0.8673 | 0.8305 | 0.9655   |
| 0.0796        | 23.08 | 900  | 0.2429          | 0.8167    | 0.8673 | 0.8412 | 0.9690   |
| 0.0043        | 25.64 | 1000 | 0.2304          | 0.8684    | 0.8761 | 0.8722 | 0.9735   |
| 0.0043        | 28.21 | 1100 | 0.2704          | 0.7823    | 0.8584 | 0.8186 | 0.9655   |
| 0.0043        | 30.77 | 1200 | 0.2647          | 0.8033    | 0.8673 | 0.8340 | 0.9673   |
| 0.0043        | 33.33 | 1300 | 0.2509          | 0.8115    | 0.8761 | 0.8426 | 0.9681   |
| 0.0043        | 35.9  | 1400 | 0.2561          | 0.7967    | 0.8673 | 0.8305 | 0.9664   |
| 0.0014        | 38.46 | 1500 | 0.2774          | 0.7823    | 0.8584 | 0.8186 | 0.9664   |
| 0.0014        | 41.03 | 1600 | 0.2580          | 0.7951    | 0.8584 | 0.8255 | 0.9673   |
| 0.0014        | 43.59 | 1700 | 0.2688          | 0.7937    | 0.8850 | 0.8368 | 0.9673   |
| 0.0014        | 46.15 | 1800 | 0.2706          | 0.8       | 0.8850 | 0.8403 | 0.9681   |
| 0.0014        | 48.72 | 1900 | 0.2608          | 0.8130    | 0.8850 | 0.8475 | 0.9690   |
| 0.0008        | 51.28 | 2000 | 0.2592          | 0.8130    | 0.8850 | 0.8475 | 0.9690   |


### Framework versions

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