---
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_v1
  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_v1

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: 0.2030
- Precision: 0.8
- Recall: 0.8319
- F1: 0.8156
- Accuracy: 0.9743

## 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-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: 3000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 2.27  | 100  | 0.3343          | 0.2051    | 0.0354 | 0.0604 | 0.8943   |
| No log        | 4.55  | 200  | 0.1934          | 0.7143    | 0.6858 | 0.6998 | 0.9524   |
| No log        | 6.82  | 300  | 0.1541          | 0.7344    | 0.7832 | 0.7580 | 0.9590   |
| No log        | 9.09  | 400  | 0.1375          | 0.7542    | 0.8009 | 0.7768 | 0.9648   |
| 0.2233        | 11.36 | 500  | 0.1323          | 0.7915    | 0.8230 | 0.8069 | 0.9695   |
| 0.2233        | 13.64 | 600  | 0.1395          | 0.8       | 0.8142 | 0.8070 | 0.9695   |
| 0.2233        | 15.91 | 700  | 0.1495          | 0.7773    | 0.8186 | 0.7974 | 0.9686   |
| 0.2233        | 18.18 | 800  | 0.1444          | 0.8103    | 0.8319 | 0.8210 | 0.9752   |
| 0.2233        | 20.45 | 900  | 0.1732          | 0.7550    | 0.8319 | 0.7916 | 0.9676   |
| 0.0375        | 22.73 | 1000 | 0.1553          | 0.7966    | 0.8319 | 0.8139 | 0.9743   |
| 0.0375        | 25.0  | 1100 | 0.1639          | 0.7924    | 0.8274 | 0.8095 | 0.9724   |
| 0.0375        | 27.27 | 1200 | 0.1598          | 0.8034    | 0.8319 | 0.8174 | 0.9752   |
| 0.0375        | 29.55 | 1300 | 0.1723          | 0.8069    | 0.8319 | 0.8192 | 0.9743   |
| 0.0375        | 31.82 | 1400 | 0.1929          | 0.7810    | 0.8363 | 0.8077 | 0.9724   |
| 0.0188        | 34.09 | 1500 | 0.1940          | 0.7866    | 0.8319 | 0.8086 | 0.9714   |
| 0.0188        | 36.36 | 1600 | 0.1904          | 0.7932    | 0.8319 | 0.8121 | 0.9724   |
| 0.0188        | 38.64 | 1700 | 0.1910          | 0.7899    | 0.8319 | 0.8103 | 0.9724   |
| 0.0188        | 40.91 | 1800 | 0.2083          | 0.7801    | 0.8319 | 0.8051 | 0.9705   |
| 0.0188        | 43.18 | 1900 | 0.1880          | 0.8       | 0.8319 | 0.8156 | 0.9743   |
| 0.0123        | 45.45 | 2000 | 0.1902          | 0.8069    | 0.8319 | 0.8192 | 0.9752   |
| 0.0123        | 47.73 | 2100 | 0.1894          | 0.8095    | 0.8274 | 0.8184 | 0.9752   |
| 0.0123        | 50.0  | 2200 | 0.1833          | 0.8210    | 0.8319 | 0.8264 | 0.9771   |
| 0.0123        | 52.27 | 2300 | 0.1911          | 0.8069    | 0.8319 | 0.8192 | 0.9752   |
| 0.0123        | 54.55 | 2400 | 0.1972          | 0.8       | 0.8319 | 0.8156 | 0.9743   |
| 0.0086        | 56.82 | 2500 | 0.1924          | 0.8139    | 0.8319 | 0.8228 | 0.9762   |
| 0.0086        | 59.09 | 2600 | 0.1983          | 0.8       | 0.8319 | 0.8156 | 0.9743   |
| 0.0086        | 61.36 | 2700 | 0.2033          | 0.8       | 0.8319 | 0.8156 | 0.9743   |
| 0.0086        | 63.64 | 2800 | 0.2039          | 0.8       | 0.8319 | 0.8156 | 0.9743   |
| 0.0086        | 65.91 | 2900 | 0.2026          | 0.8       | 0.8319 | 0.8156 | 0.9743   |
| 0.0084        | 68.18 | 3000 | 0.2030          | 0.8       | 0.8319 | 0.8156 | 0.9743   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2