---
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
  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

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: 0.2507
- Precision: 0.8319
- Recall: 0.8319
- F1: 0.8319
- Accuracy: 0.9771

## 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: 3000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 2.27  | 100  | 0.1116          | 0.7705    | 0.8319 | 0.8    | 0.9676   |
| No log        | 4.55  | 200  | 0.1130          | 0.8319    | 0.8540 | 0.8428 | 0.9762   |
| No log        | 6.82  | 300  | 0.1707          | 0.7931    | 0.8142 | 0.8035 | 0.9686   |
| No log        | 9.09  | 400  | 0.1998          | 0.7521    | 0.7920 | 0.7716 | 0.9648   |
| 0.0744        | 11.36 | 500  | 0.1633          | 0.8210    | 0.8319 | 0.8264 | 0.9752   |
| 0.0744        | 13.64 | 600  | 0.1784          | 0.8182    | 0.8363 | 0.8271 | 0.9752   |
| 0.0744        | 15.91 | 700  | 0.1909          | 0.8095    | 0.8274 | 0.8184 | 0.9724   |
| 0.0744        | 18.18 | 800  | 0.1962          | 0.7974    | 0.8186 | 0.8079 | 0.9724   |
| 0.0744        | 20.45 | 900  | 0.1723          | 0.8412    | 0.8673 | 0.8540 | 0.9781   |
| 0.0081        | 22.73 | 1000 | 0.2109          | 0.8210    | 0.8319 | 0.8264 | 0.9733   |
| 0.0081        | 25.0  | 1100 | 0.2194          | 0.8087    | 0.8230 | 0.8158 | 0.9743   |
| 0.0081        | 27.27 | 1200 | 0.2076          | 0.8465    | 0.8540 | 0.8502 | 0.9771   |
| 0.0081        | 29.55 | 1300 | 0.1883          | 0.8688    | 0.8496 | 0.8591 | 0.9819   |
| 0.0081        | 31.82 | 1400 | 0.2042          | 0.8170    | 0.8496 | 0.8330 | 0.9771   |
| 0.0034        | 34.09 | 1500 | 0.2144          | 0.8261    | 0.8407 | 0.8333 | 0.9771   |
| 0.0034        | 36.36 | 1600 | 0.1953          | 0.8205    | 0.8496 | 0.8348 | 0.9771   |
| 0.0034        | 38.64 | 1700 | 0.2259          | 0.8267    | 0.8230 | 0.8248 | 0.9762   |
| 0.0034        | 40.91 | 1800 | 0.2553          | 0.7974    | 0.8186 | 0.8079 | 0.9714   |
| 0.0034        | 43.18 | 1900 | 0.2238          | 0.8377    | 0.8451 | 0.8414 | 0.9781   |
| 0.0006        | 45.45 | 2000 | 0.2245          | 0.8451    | 0.8451 | 0.8451 | 0.9790   |
| 0.0006        | 47.73 | 2100 | 0.2389          | 0.8326    | 0.8142 | 0.8233 | 0.9762   |
| 0.0006        | 50.0  | 2200 | 0.2500          | 0.8251    | 0.8142 | 0.8196 | 0.9752   |
| 0.0006        | 52.27 | 2300 | 0.2537          | 0.8304    | 0.8451 | 0.8377 | 0.9762   |
| 0.0006        | 54.55 | 2400 | 0.2410          | 0.8319    | 0.8319 | 0.8319 | 0.9771   |
| 0.0001        | 56.82 | 2500 | 0.2484          | 0.8319    | 0.8319 | 0.8319 | 0.9771   |
| 0.0001        | 59.09 | 2600 | 0.2517          | 0.8319    | 0.8319 | 0.8319 | 0.9771   |
| 0.0001        | 61.36 | 2700 | 0.2524          | 0.8319    | 0.8319 | 0.8319 | 0.9771   |
| 0.0001        | 63.64 | 2800 | 0.2531          | 0.8319    | 0.8319 | 0.8319 | 0.9771   |
| 0.0001        | 65.91 | 2900 | 0.2528          | 0.8319    | 0.8319 | 0.8319 | 0.9771   |
| 0.0           | 68.18 | 3000 | 0.2507          | 0.8319    | 0.8319 | 0.8319 | 0.9771   |


### Framework versions

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