---
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-v2-4000
  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-v2-4000

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: 0.0153
- 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        | 0.2618 | 100  | 0.8437          | 0.9605    | 0.9605 | 0.9605 | 0.6867   |
| No log        | 0.5236 | 200  | 0.5414          | 0.9962    | 0.9981 | 0.9972 | 0.8052   |
| No log        | 0.7853 | 300  | 0.1877          | 0.9944    | 0.9962 | 0.9953 | 0.9838   |
| No log        | 1.0471 | 400  | 0.0502          | 1.0       | 1.0    | 1.0    | 0.9903   |
| 0.5339        | 1.3089 | 500  | 0.0153          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.5339        | 1.5707 | 600  | 0.0085          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.5339        | 1.8325 | 700  | 0.0062          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.5339        | 2.0942 | 800  | 0.0049          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.5339        | 2.3560 | 900  | 0.0041          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.0125        | 2.6178 | 1000 | 0.0035          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.0125        | 2.8796 | 1100 | 0.0031          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.0125        | 3.1414 | 1200 | 0.0028          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.0125        | 3.4031 | 1300 | 0.0026          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.0125        | 3.6649 | 1400 | 0.0024          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.0052        | 3.9267 | 1500 | 0.0022          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.0052        | 4.1885 | 1600 | 0.0021          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.0052        | 4.4503 | 1700 | 0.0020          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.0052        | 4.7120 | 1800 | 0.0020          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.0052        | 4.9738 | 1900 | 0.0019          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.004         | 5.2356 | 2000 | 0.0019          | 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