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

# ser-model-microsoft

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: 0.2762
- Precision: 0.6
- Recall: 0.9
- F1: 0.7200
- Accuracy: 0.925

## 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 5.0   | 10   | 0.9255          | 0.0       | 0.0    | 0.0    | 0.7      |
| No log        | 10.0  | 20   | 0.6668          | 0.4444    | 0.4    | 0.4211 | 0.7875   |
| No log        | 15.0  | 30   | 0.4304          | 0.6667    | 0.8    | 0.7273 | 0.85     |
| No log        | 20.0  | 40   | 0.4050          | 0.6667    | 0.8    | 0.7273 | 0.85     |
| No log        | 25.0  | 50   | 0.5639          | 0.8       | 0.8    | 0.8000 | 0.8125   |
| No log        | 30.0  | 60   | 0.2429          | 0.8       | 0.8    | 0.8000 | 0.925    |
| No log        | 35.0  | 70   | 0.4434          | 0.6667    | 0.8    | 0.7273 | 0.8625   |
| No log        | 40.0  | 80   | 0.2817          | 0.6       | 0.9    | 0.7200 | 0.925    |
| No log        | 45.0  | 90   | 0.2784          | 0.6       | 0.9    | 0.7200 | 0.925    |
| No log        | 50.0  | 100  | 0.2762          | 0.6       | 0.9    | 0.7200 | 0.925    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1