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---
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: 0.9845822875582646
- name: Recall
type: recall
value: 0.989193083573487
- name: F1
type: f1
value: 0.9868823000898472
- name: Accuracy
type: accuracy
value: 0.9908389585342333
---
<!-- 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: 0.0558
- Precision: 0.9846
- Recall: 0.9892
- F1: 0.9869
- Accuracy: 0.9908
## 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 | 0.2662 | 0.9524 | 0.9442 | 0.9483 | 0.9566 |
| No log | 4.26 | 200 | 0.1026 | 0.9771 | 0.9820 | 0.9795 | 0.9851 |
| No log | 6.38 | 300 | 0.0722 | 0.9821 | 0.9878 | 0.9849 | 0.9884 |
| No log | 8.51 | 400 | 0.0608 | 0.9852 | 0.9863 | 0.9858 | 0.9892 |
| 0.2962 | 10.64 | 500 | 0.0606 | 0.9849 | 0.9860 | 0.9854 | 0.9889 |
| 0.2962 | 12.77 | 600 | 0.0518 | 0.9860 | 0.9910 | 0.9885 | 0.9920 |
| 0.2962 | 14.89 | 700 | 0.0526 | 0.9864 | 0.9910 | 0.9887 | 0.9923 |
| 0.2962 | 17.02 | 800 | 0.0543 | 0.9849 | 0.9896 | 0.9872 | 0.9913 |
| 0.2962 | 19.15 | 900 | 0.0557 | 0.9846 | 0.9888 | 0.9867 | 0.9911 |
| 0.0255 | 21.28 | 1000 | 0.0558 | 0.9846 | 0.9892 | 0.9869 | 0.9908 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.2
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