---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: model-2024-06-06
  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. -->

# model-2024-06-06

This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5257
- Precision: 0.7422
- Recall: 0.7427
- F1: 0.7424
- Accuracy: 0.8617

## 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        | 0.6   | 100  | 1.4725          | 0.2387    | 0.0987 | 0.1396 | 0.6316   |
| No log        | 1.19  | 200  | 0.9815          | 0.5362    | 0.434  | 0.4797 | 0.7585   |
| No log        | 1.79  | 300  | 0.7596          | 0.6422    | 0.5707 | 0.6043 | 0.8071   |
| No log        | 2.38  | 400  | 0.6719          | 0.6739    | 0.6433 | 0.6583 | 0.8240   |
| 1.1397        | 2.98  | 500  | 0.5865          | 0.7118    | 0.7013 | 0.7065 | 0.8429   |
| 1.1397        | 3.57  | 600  | 0.5910          | 0.7293    | 0.722  | 0.7256 | 0.8505   |
| 1.1397        | 4.17  | 700  | 0.5456          | 0.7373    | 0.726  | 0.7316 | 0.8524   |
| 1.1397        | 4.76  | 800  | 0.5343          | 0.7376    | 0.7327 | 0.7351 | 0.8557   |
| 1.1397        | 5.36  | 900  | 0.5327          | 0.7283    | 0.7487 | 0.7383 | 0.8569   |
| 0.4593        | 5.95  | 1000 | 0.5257          | 0.7422    | 0.7427 | 0.7424 | 0.8617   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.13.3