---
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_thursday_oct4_v7
  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_thursday_oct4_v7

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: 0.2861
- Precision: 0.8352
- Recall: 0.7894
- F1: 0.8116
- Accuracy: 0.9586

## 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        | 1.12  | 100  | 0.2568          | 0.8574    | 0.7770 | 0.8152 | 0.9586   |
| No log        | 2.25  | 200  | 0.2653          | 0.8268    | 0.7858 | 0.8058 | 0.9581   |
| No log        | 3.37  | 300  | 0.2728          | 0.7982    | 0.7770 | 0.7874 | 0.9565   |
| No log        | 4.49  | 400  | 0.2626          | 0.8569    | 0.7735 | 0.8130 | 0.9589   |
| 0.114         | 5.62  | 500  | 0.2861          | 0.8352    | 0.7894 | 0.8116 | 0.9586   |
| 0.114         | 6.74  | 600  | 0.2978          | 0.8205    | 0.7929 | 0.8065 | 0.9582   |
| 0.114         | 7.87  | 700  | 0.2942          | 0.8256    | 0.7876 | 0.8062 | 0.9584   |
| 0.114         | 8.99  | 800  | 0.2910          | 0.8420    | 0.7735 | 0.8063 | 0.9579   |
| 0.114         | 10.11 | 900  | 0.3028          | 0.8346    | 0.7770 | 0.8048 | 0.9574   |
| 0.0846        | 11.24 | 1000 | 0.2989          | 0.8318    | 0.7876 | 0.8091 | 0.9581   |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0