---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-language-levels-v2
  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-finetuned-language-levels-v2

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0006
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0

## 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: 2000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log        | 0.0320 | 100  | 0.0058          | 1.0       | 1.0    | 1.0 | 1.0      |
| No log        | 0.0640 | 200  | 0.0022          | 1.0       | 1.0    | 1.0 | 1.0      |
| No log        | 0.0959 | 300  | 0.0013          | 1.0       | 1.0    | 1.0 | 1.0      |
| No log        | 0.1279 | 400  | 0.0009          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0705        | 0.1599 | 500  | 0.0006          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0705        | 0.1919 | 600  | 0.0005          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0705        | 0.2239 | 700  | 0.0004          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0705        | 0.2558 | 800  | 0.0003          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0705        | 0.2878 | 900  | 0.0003          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0006        | 0.3198 | 1000 | 0.0003          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0006        | 0.3518 | 1100 | 0.0002          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0006        | 0.3838 | 1200 | 0.0002          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0006        | 0.4157 | 1300 | 0.0002          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0006        | 0.4477 | 1400 | 0.0002          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0003        | 0.4797 | 1500 | 0.0002          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0003        | 0.5117 | 1600 | 0.0002          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0003        | 0.5437 | 1700 | 0.0002          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0003        | 0.5756 | 1800 | 0.0002          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0003        | 0.6076 | 1900 | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0002        | 0.6396 | 2000 | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |


### Framework versions

- Transformers 4.43.2
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1