---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- nielsr/funsd-layoutlmv3
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: pasha
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: nielsr/funsd-layoutlmv3
      type: nielsr/funsd-layoutlmv3
      config: pasha
      split: test
      args: pasha
    metrics:
    - name: Precision
      type: precision
      value: 0.986704994610133
    - name: Recall
      type: recall
      value: 0.989193083573487
    - name: F1
      type: f1
      value: 0.9879474725670084
    - name: Accuracy
      type: accuracy
      value: 0.9905978784956606
---

<!-- 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. -->

# pasha

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the nielsr/funsd-layoutlmv3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0585
- Precision: 0.9867
- Recall: 0.9892
- F1: 0.9879
- Accuracy: 0.9906

## 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: 16
- eval_batch_size: 16
- 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        | 2.13  | 100  | 0.2664          | 0.9534    | 0.9438 | 0.9486 | 0.9571   |
| No log        | 4.26  | 200  | 0.1044          | 0.9756    | 0.9802 | 0.9779 | 0.9838   |
| No log        | 6.38  | 300  | 0.0672          | 0.9853    | 0.9899 | 0.9876 | 0.9904   |
| No log        | 8.51  | 400  | 0.0634          | 0.9824    | 0.9860 | 0.9842 | 0.9884   |
| 0.2958        | 10.64 | 500  | 0.0585          | 0.9867    | 0.9892 | 0.9879 | 0.9906   |
| 0.2958        | 12.77 | 600  | 0.0511          | 0.9889    | 0.9928 | 0.9908 | 0.9928   |
| 0.2958        | 14.89 | 700  | 0.0503          | 0.9871    | 0.9921 | 0.9896 | 0.9925   |
| 0.2958        | 17.02 | 800  | 0.0529          | 0.9860    | 0.9903 | 0.9881 | 0.9913   |
| 0.2958        | 19.15 | 900  | 0.0581          | 0.9842    | 0.9892 | 0.9867 | 0.9904   |
| 0.0256        | 21.28 | 1000 | 0.0571          | 0.9849    | 0.9888 | 0.9869 | 0.9901   |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.2