---
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-v3-4000
  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-v3-4000

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: 0.0209
- 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: 1000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 0.0290 | 100  | 0.8242          | 0.9549    | 0.9520 | 0.9534 | 0.7171   |
| No log        | 0.0579 | 200  | 0.5708          | 0.9636    | 0.9772 | 0.9703 | 0.7951   |
| No log        | 0.0869 | 300  | 0.3493          | 0.9993    | 0.9993 | 0.9993 | 0.8839   |
| No log        | 0.1158 | 400  | 0.1466          | 0.9998    | 0.9998 | 0.9998 | 0.9752   |
| 0.6024        | 0.1448 | 500  | 0.0689          | 0.9965    | 0.9972 | 0.9969 | 0.9823   |
| 0.6024        | 0.1738 | 600  | 0.0442          | 1.0       | 1.0    | 1.0    | 0.9946   |
| 0.6024        | 0.2027 | 700  | 0.0360          | 1.0       | 1.0    | 1.0    | 0.9847   |
| 0.6024        | 0.2317 | 800  | 0.0280          | 1.0       | 1.0    | 1.0    | 0.9972   |
| 0.6024        | 0.2606 | 900  | 0.0247          | 1.0       | 1.0    | 1.0    | 0.9953   |
| 0.0516        | 0.2896 | 1000 | 0.0209          | 1.0       | 1.0    | 1.0    | 1.0      |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1