---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: LayoutLM_4
  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. -->

# LayoutLM_4

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6673
- Precision: 0.675
- Recall: 0.3576
- F1: 0.4675
- Accuracy: 0.8559

## 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-06
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1500

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 7.14   | 100  | 1.2248          | 0.0       | 0.0    | 0.0    | 0.7818   |
| No log        | 14.29  | 200  | 0.9800          | 0.0       | 0.0    | 0.0    | 0.7818   |
| No log        | 21.43  | 300  | 0.8988          | 0.0       | 0.0    | 0.0    | 0.7818   |
| No log        | 28.57  | 400  | 0.8416          | 0.0       | 0.0    | 0.0    | 0.7818   |
| 1.0601        | 35.71  | 500  | 0.8025          | 0.0       | 0.0    | 0.0    | 0.7818   |
| 1.0601        | 42.86  | 600  | 0.7719          | 0.0       | 0.0    | 0.0    | 0.7818   |
| 1.0601        | 50.0   | 700  | 0.7428          | 0.75      | 0.0397 | 0.0755 | 0.7902   |
| 1.0601        | 57.14  | 800  | 0.7225          | 0.5714    | 0.0530 | 0.0970 | 0.7972   |
| 1.0601        | 64.29  | 900  | 0.7107          | 0.6923    | 0.1192 | 0.2034 | 0.8140   |
| 0.6088        | 71.43  | 1000 | 0.6954          | 0.6444    | 0.1921 | 0.2959 | 0.8308   |
| 0.6088        | 78.57  | 1100 | 0.6861          | 0.6727    | 0.2450 | 0.3592 | 0.8392   |
| 0.6088        | 85.71  | 1200 | 0.6800          | 0.6719    | 0.2848 | 0.4    | 0.8462   |
| 0.6088        | 92.86  | 1300 | 0.6694          | 0.6901    | 0.3245 | 0.4414 | 0.8517   |
| 0.6088        | 100.0  | 1400 | 0.6684          | 0.675     | 0.3576 | 0.4675 | 0.8573   |
| 0.5237        | 107.14 | 1500 | 0.6673          | 0.675     | 0.3576 | 0.4675 | 0.8559   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3