---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-final-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. -->

# layoutlmv3-final-v1

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: 0.0822
- Precision: 0.9789
- Recall: 0.9839
- F1: 0.9814
- Accuracy: 0.9852

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 2.56  | 100  | 1.7056          | 0.4839    | 0.5464 | 0.5133 | 0.6494   |
| No log        | 5.13  | 200  | 0.4856          | 0.8255    | 0.8821 | 0.8528 | 0.9217   |
| No log        | 7.69  | 300  | 0.2319          | 0.9027    | 0.9355 | 0.9188 | 0.9575   |
| No log        | 10.26 | 400  | 0.1437          | 0.9652    | 0.9778 | 0.9715 | 0.9800   |
| 0.9248        | 12.82 | 500  | 0.1204          | 0.967     | 0.9748 | 0.9709 | 0.9770   |
| 0.9248        | 15.38 | 600  | 0.1025          | 0.9711    | 0.9808 | 0.9759 | 0.9790   |
| 0.9248        | 17.95 | 700  | 0.0971          | 0.9789    | 0.9829 | 0.9809 | 0.9826   |
| 0.9248        | 20.51 | 800  | 0.0885          | 0.9819    | 0.9849 | 0.9834 | 0.9846   |
| 0.9248        | 23.08 | 900  | 0.0858          | 0.9789    | 0.9839 | 0.9814 | 0.9857   |
| 0.0697        | 25.64 | 1000 | 0.0822          | 0.9789    | 0.9839 | 0.9814 | 0.9852   |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 1.8.0+cu101
- Datasets 2.12.0
- Tokenizers 0.13.3