---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv2-base-uncased
tags:
- generated_from_trainer
model-index:
- name: layoutlmv2-base-uncased_finetuned_docvqa_v2
  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. -->

# layoutlmv2-base-uncased_finetuned_docvqa_v2

This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4977

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 5.1316        | 0.44  | 50   | 4.3296          |
| 4.3071        | 0.88  | 100  | 3.9311          |
| 3.8545        | 1.33  | 150  | 3.7061          |
| 3.6578        | 1.77  | 200  | 3.5642          |
| 3.2506        | 2.21  | 250  | 3.3789          |
| 2.9991        | 2.65  | 300  | 3.1969          |
| 2.7893        | 3.1   | 350  | 3.2842          |
| 2.3975        | 3.54  | 400  | 2.8765          |
| 2.1188        | 3.98  | 450  | 3.0513          |
| 1.9405        | 4.42  | 500  | 2.6575          |
| 1.7123        | 4.87  | 550  | 2.8113          |
| 1.6361        | 5.31  | 600  | 2.6848          |
| 1.5425        | 5.75  | 650  | 2.7986          |
| 1.2871        | 6.19  | 700  | 2.9508          |
| 1.1132        | 6.64  | 750  | 2.7070          |
| 1.1105        | 7.08  | 800  | 2.6293          |
| 0.8855        | 7.52  | 850  | 2.9005          |
| 0.9427        | 7.96  | 900  | 2.4977          |
| 0.8359        | 8.41  | 950  | 2.7100          |
| 0.7038        | 8.85  | 1000 | 2.8090          |
| 0.7068        | 9.29  | 1050 | 2.8265          |
| 0.7037        | 9.73  | 1100 | 2.8136          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1