---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Output_LayoutLMv3_v3
  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. -->

# Output_LayoutLMv3_v3

This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1344
- Precision: 0.7699
- Recall: 0.8142
- F1: 0.7914
- Accuracy: 0.9695

## 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-07
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 3000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 4.55   | 100  | 0.5786          | 0.0       | 0.0    | 0.0    | 0.8867   |
| No log        | 9.09   | 200  | 0.4032          | 0.0       | 0.0    | 0.0    | 0.8867   |
| No log        | 13.64  | 300  | 0.2908          | 0.4091    | 0.1593 | 0.2293 | 0.9067   |
| No log        | 18.18  | 400  | 0.2300          | 0.5858    | 0.4381 | 0.5013 | 0.9267   |
| 0.5251        | 22.73  | 500  | 0.1981          | 0.685     | 0.6062 | 0.6432 | 0.9438   |
| 0.5251        | 27.27  | 600  | 0.1790          | 0.7130    | 0.6814 | 0.6968 | 0.9505   |
| 0.5251        | 31.82  | 700  | 0.1689          | 0.7249    | 0.7345 | 0.7297 | 0.9581   |
| 0.5251        | 36.36  | 800  | 0.1593          | 0.7478    | 0.7478 | 0.7478 | 0.9619   |
| 0.5251        | 40.91  | 900  | 0.1582          | 0.75      | 0.7832 | 0.7662 | 0.9638   |
| 0.129         | 45.45  | 1000 | 0.1527          | 0.7306    | 0.7920 | 0.7601 | 0.9619   |
| 0.129         | 50.0   | 1100 | 0.1470          | 0.7429    | 0.8053 | 0.7728 | 0.9638   |
| 0.129         | 54.55  | 1200 | 0.1418          | 0.7552    | 0.8053 | 0.7794 | 0.9657   |
| 0.129         | 59.09  | 1300 | 0.1404          | 0.7657    | 0.8097 | 0.7871 | 0.9667   |
| 0.129         | 63.64  | 1400 | 0.1368          | 0.7741    | 0.8186 | 0.7957 | 0.9695   |
| 0.0799        | 68.18  | 1500 | 0.1316          | 0.7741    | 0.8186 | 0.7957 | 0.9705   |
| 0.0799        | 72.73  | 1600 | 0.1301          | 0.7764    | 0.8142 | 0.7948 | 0.9705   |
| 0.0799        | 77.27  | 1700 | 0.1326          | 0.7699    | 0.8142 | 0.7914 | 0.9695   |
| 0.0799        | 81.82  | 1800 | 0.1357          | 0.7552    | 0.8053 | 0.7794 | 0.9676   |
| 0.0799        | 86.36  | 1900 | 0.1304          | 0.7699    | 0.8142 | 0.7914 | 0.9695   |
| 0.0561        | 90.91  | 2000 | 0.1326          | 0.7699    | 0.8142 | 0.7914 | 0.9695   |
| 0.0561        | 95.45  | 2100 | 0.1340          | 0.7689    | 0.8097 | 0.7888 | 0.9695   |
| 0.0561        | 100.0  | 2200 | 0.1371          | 0.7635    | 0.8142 | 0.7880 | 0.9686   |
| 0.0561        | 104.55 | 2300 | 0.1337          | 0.7764    | 0.8142 | 0.7948 | 0.9705   |
| 0.0561        | 109.09 | 2400 | 0.1310          | 0.7764    | 0.8142 | 0.7948 | 0.9705   |
| 0.0451        | 113.64 | 2500 | 0.1353          | 0.7657    | 0.8097 | 0.7871 | 0.9686   |
| 0.0451        | 118.18 | 2600 | 0.1357          | 0.7657    | 0.8097 | 0.7871 | 0.9686   |
| 0.0451        | 122.73 | 2700 | 0.1361          | 0.7699    | 0.8142 | 0.7914 | 0.9695   |
| 0.0451        | 127.27 | 2800 | 0.1358          | 0.7667    | 0.8142 | 0.7897 | 0.9686   |
| 0.0451        | 131.82 | 2900 | 0.1347          | 0.7699    | 0.8142 | 0.7914 | 0.9695   |
| 0.0414        | 136.36 | 3000 | 0.1344          | 0.7699    | 0.8142 | 0.7914 | 0.9695   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2