---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-funsd
  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. -->

# layoutlmv3-finetuned-funsd

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6016
- Precision: 0.8712
- Recall: 0.903
- F1: 0.8868
- Accuracy: 0.8414

## 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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.67  | 25   | 1.1945          | 0.4801    | 0.5295 | 0.5036 | 0.6659   |
| No log        | 3.33  | 50   | 0.7770          | 0.7472    | 0.807  | 0.7760 | 0.7687   |
| No log        | 5.0   | 75   | 0.5990          | 0.7965    | 0.8515 | 0.8231 | 0.8119   |
| No log        | 6.67  | 100  | 0.6814          | 0.8061    | 0.879  | 0.8409 | 0.7702   |
| No log        | 8.33  | 125  | 0.5392          | 0.8172    | 0.8785 | 0.8467 | 0.8316   |
| No log        | 10.0  | 150  | 0.5438          | 0.8352    | 0.887  | 0.8603 | 0.8114   |
| No log        | 11.67 | 175  | 0.5430          | 0.8586    | 0.8925 | 0.8752 | 0.8382   |
| No log        | 13.33 | 200  | 0.5897          | 0.8521    | 0.887  | 0.8692 | 0.8258   |
| No log        | 15.0  | 225  | 0.5427          | 0.86      | 0.903  | 0.8810 | 0.8430   |
| No log        | 16.67 | 250  | 0.5542          | 0.8713    | 0.8935 | 0.8823 | 0.8411   |
| No log        | 18.33 | 275  | 0.6014          | 0.8632    | 0.902  | 0.8822 | 0.8321   |
| No log        | 20.0  | 300  | 0.5971          | 0.8691    | 0.9    | 0.8843 | 0.8366   |
| No log        | 21.67 | 325  | 0.5983          | 0.8800    | 0.8985 | 0.8892 | 0.8313   |
| No log        | 23.33 | 350  | 0.5867          | 0.8842    | 0.909  | 0.8964 | 0.8414   |
| No log        | 25.0  | 375  | 0.5948          | 0.8797    | 0.9065 | 0.8929 | 0.8466   |
| No log        | 26.67 | 400  | 0.6016          | 0.8712    | 0.903  | 0.8868 | 0.8414   |


### Framework versions

- Transformers 4.12.5
- Pytorch 1.10.0+cu111
- Datasets 2.13.2
- Tokenizers 0.10.1