---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-Algo_427Images
  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-Algo_427Images

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: 0.0013
- Precision: 0.9937
- Recall: 0.9964
- F1: 0.9950
- Accuracy: 0.9999

## 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: 4
- eval_batch_size: 4
- 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        | 1.25  | 100  | 0.0082          | 0.9505    | 0.9367 | 0.9435 | 0.9983   |
| No log        | 2.5   | 200  | 0.0024          | 0.9883    | 0.9901 | 0.9892 | 0.9997   |
| No log        | 3.75  | 300  | 0.0020          | 0.9883    | 0.9919 | 0.9901 | 0.9997   |
| No log        | 5.0   | 400  | 0.0016          | 0.9910    | 0.9928 | 0.9919 | 0.9998   |
| 0.0301        | 6.25  | 500  | 0.0015          | 0.9910    | 0.9928 | 0.9919 | 0.9998   |
| 0.0301        | 7.5   | 600  | 0.0014          | 0.9928    | 0.9946 | 0.9937 | 0.9998   |
| 0.0301        | 8.75  | 700  | 0.0013          | 0.9928    | 0.9946 | 0.9937 | 0.9998   |
| 0.0301        | 10.0  | 800  | 0.0013          | 0.9937    | 0.9964 | 0.9950 | 0.9999   |
| 0.0301        | 11.25 | 900  | 0.0013          | 0.9928    | 0.9946 | 0.9937 | 0.9998   |
| 0.002         | 12.5  | 1000 | 0.0013          | 0.9937    | 0.9964 | 0.9950 | 0.9999   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3