---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: LayoutLMv3_5_entities_3
  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_3

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: 0.2107
- Precision: 0.8835
- Recall: 0.8426
- F1: 0.8626
- Accuracy: 0.9729

## 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: 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  | 0.1391          | 0.78      | 0.7222 | 0.7500 | 0.9575   |
| No log        | 5.13  | 200  | 0.1103          | 0.8725    | 0.8241 | 0.8476 | 0.9720   |
| No log        | 7.69  | 300  | 0.1415          | 0.8922    | 0.8426 | 0.8667 | 0.9739   |
| No log        | 10.26 | 400  | 0.1649          | 0.8378    | 0.8611 | 0.8493 | 0.9710   |
| 0.0838        | 12.82 | 500  | 0.1545          | 0.8713    | 0.8148 | 0.8421 | 0.9729   |
| 0.0838        | 15.38 | 600  | 0.1396          | 0.8545    | 0.8704 | 0.8624 | 0.9749   |
| 0.0838        | 17.95 | 700  | 0.1523          | 0.8942    | 0.8611 | 0.8774 | 0.9768   |
| 0.0838        | 20.51 | 800  | 0.1718          | 0.8519    | 0.8519 | 0.8519 | 0.9710   |
| 0.0838        | 23.08 | 900  | 0.2242          | 0.87      | 0.8056 | 0.8365 | 0.9700   |
| 0.0044        | 25.64 | 1000 | 0.2165          | 0.88      | 0.8148 | 0.8462 | 0.9710   |
| 0.0044        | 28.21 | 1100 | 0.2235          | 0.8866    | 0.7963 | 0.8390 | 0.9681   |
| 0.0044        | 30.77 | 1200 | 0.2174          | 0.9       | 0.8333 | 0.8654 | 0.9739   |
| 0.0044        | 33.33 | 1300 | 0.1991          | 0.8692    | 0.8611 | 0.8651 | 0.9729   |
| 0.0044        | 35.9  | 1400 | 0.1986          | 0.8762    | 0.8519 | 0.8638 | 0.9739   |
| 0.0015        | 38.46 | 1500 | 0.2061          | 0.8713    | 0.8148 | 0.8421 | 0.9700   |
| 0.0015        | 41.03 | 1600 | 0.1970          | 0.8641    | 0.8241 | 0.8436 | 0.9710   |
| 0.0015        | 43.59 | 1700 | 0.2127          | 0.8614    | 0.8056 | 0.8325 | 0.9700   |
| 0.0015        | 46.15 | 1800 | 0.2070          | 0.875     | 0.8426 | 0.8585 | 0.9729   |
| 0.0015        | 48.72 | 1900 | 0.2097          | 0.8835    | 0.8426 | 0.8626 | 0.9729   |
| 0.0008        | 51.28 | 2000 | 0.2107          | 0.8835    | 0.8426 | 0.8626 | 0.9729   |


### Framework versions

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