---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutmlv3_sunday_sep3_v5
  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. -->

# layoutmlv3_sunday_sep3_v5

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: 0.1630
- Precision: 0.6867
- Recall: 0.7308
- F1: 0.7081
- Accuracy: 0.9570

## 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        | 8.33  | 100  | 0.5150          | 0.5139    | 0.4744 | 0.4933 | 0.8460   |
| No log        | 16.67 | 200  | 0.2462          | 0.5053    | 0.6154 | 0.5549 | 0.9387   |
| No log        | 25.0  | 300  | 0.1973          | 0.6471    | 0.7051 | 0.6748 | 0.9536   |
| No log        | 33.33 | 400  | 0.1617          | 0.6667    | 0.7179 | 0.6914 | 0.9520   |
| 0.3718        | 41.67 | 500  | 0.1630          | 0.6867    | 0.7308 | 0.7081 | 0.9570   |
| 0.3718        | 50.0  | 600  | 0.2247          | 0.5106    | 0.6154 | 0.5581 | 0.9073   |
| 0.3718        | 58.33 | 700  | 0.3364          | 0.5393    | 0.6154 | 0.5749 | 0.8907   |
| 0.3718        | 66.67 | 800  | 0.1783          | 0.5435    | 0.6410 | 0.5882 | 0.9454   |
| 0.3718        | 75.0  | 900  | 0.2255          | 0.5263    | 0.6410 | 0.5780 | 0.9305   |
| 0.0196        | 83.33 | 1000 | 0.2781          | 0.5158    | 0.6282 | 0.5665 | 0.9123   |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3