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---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-Algo_22000Words
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-Algo_22000Words
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: 0.4487
- Precision: 0.8409
- Recall: 0.8268
- F1: 0.8338
- Accuracy: 0.8727
## 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: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 0.03 | 10 | 1.8188 | 0.1983 | 0.1285 | 0.1559 | 0.3227 |
| No log | 0.07 | 20 | 1.6701 | 0.1789 | 0.0950 | 0.1241 | 0.3364 |
| No log | 0.1 | 30 | 1.5675 | 0.3028 | 0.1844 | 0.2292 | 0.4409 |
| No log | 0.14 | 40 | 1.4618 | 0.3803 | 0.3017 | 0.3364 | 0.5182 |
| No log | 0.17 | 50 | 1.3792 | 0.4228 | 0.3520 | 0.3841 | 0.5545 |
| No log | 0.21 | 60 | 1.2919 | 0.4730 | 0.3911 | 0.4281 | 0.5727 |
| No log | 0.24 | 70 | 1.2117 | 0.5513 | 0.4804 | 0.5134 | 0.6364 |
| No log | 0.28 | 80 | 1.1297 | 0.6024 | 0.5587 | 0.5797 | 0.6909 |
| No log | 0.31 | 90 | 1.0708 | 0.6176 | 0.5866 | 0.6017 | 0.6955 |
| No log | 0.35 | 100 | 1.0096 | 0.6095 | 0.5754 | 0.5920 | 0.7091 |
| No log | 0.38 | 110 | 0.9750 | 0.5818 | 0.5363 | 0.5581 | 0.6727 |
| No log | 0.42 | 120 | 0.9478 | 0.5893 | 0.5531 | 0.5706 | 0.6818 |
| No log | 0.45 | 130 | 0.8710 | 0.6494 | 0.6313 | 0.6402 | 0.7318 |
| No log | 0.49 | 140 | 0.8509 | 0.6941 | 0.6592 | 0.6762 | 0.7636 |
| No log | 0.52 | 150 | 0.8065 | 0.6959 | 0.6648 | 0.68 | 0.7682 |
| No log | 0.56 | 160 | 0.7702 | 0.7341 | 0.7095 | 0.7216 | 0.7909 |
| No log | 0.59 | 170 | 0.7290 | 0.7529 | 0.7318 | 0.7422 | 0.8045 |
| No log | 0.63 | 180 | 0.7143 | 0.7414 | 0.7207 | 0.7309 | 0.7955 |
| No log | 0.66 | 190 | 0.7161 | 0.7557 | 0.7430 | 0.7493 | 0.8091 |
| No log | 0.7 | 200 | 0.6983 | 0.7443 | 0.7318 | 0.7380 | 0.8 |
| No log | 0.73 | 210 | 0.6654 | 0.7771 | 0.7598 | 0.7684 | 0.8273 |
| No log | 0.77 | 220 | 0.6355 | 0.7701 | 0.7486 | 0.7592 | 0.8273 |
| No log | 0.8 | 230 | 0.6380 | 0.7746 | 0.7486 | 0.7614 | 0.8182 |
| No log | 0.84 | 240 | 0.6313 | 0.7784 | 0.7654 | 0.7718 | 0.8273 |
| No log | 0.87 | 250 | 0.6356 | 0.7797 | 0.7709 | 0.7753 | 0.8318 |
| No log | 0.91 | 260 | 0.6125 | 0.7853 | 0.7765 | 0.7809 | 0.8273 |
| No log | 0.94 | 270 | 0.6109 | 0.7943 | 0.7765 | 0.7853 | 0.8364 |
| No log | 0.98 | 280 | 0.6087 | 0.7771 | 0.7598 | 0.7684 | 0.8273 |
| No log | 1.01 | 290 | 0.5677 | 0.8103 | 0.7877 | 0.7989 | 0.8455 |
| No log | 1.05 | 300 | 0.5542 | 0.8057 | 0.7877 | 0.7966 | 0.8409 |
| No log | 1.08 | 310 | 0.5490 | 0.8125 | 0.7989 | 0.8056 | 0.85 |
| No log | 1.11 | 320 | 0.5490 | 0.8023 | 0.7933 | 0.7978 | 0.8409 |
| No log | 1.15 | 330 | 0.5632 | 0.7684 | 0.7598 | 0.7640 | 0.8091 |
| No log | 1.18 | 340 | 0.5686 | 0.7809 | 0.7765 | 0.7787 | 0.8182 |
| No log | 1.22 | 350 | 0.5302 | 0.7989 | 0.7989 | 0.7989 | 0.8364 |
| No log | 1.25 | 360 | 0.5101 | 0.8146 | 0.8101 | 0.8123 | 0.8545 |
| No log | 1.29 | 370 | 0.5180 | 0.8023 | 0.7933 | 0.7978 | 0.85 |
| No log | 1.32 | 380 | 0.5088 | 0.7966 | 0.7877 | 0.7921 | 0.8409 |
| No log | 1.36 | 390 | 0.4975 | 0.8136 | 0.8045 | 0.8090 | 0.8455 |
| No log | 1.39 | 400 | 0.4914 | 0.8202 | 0.8156 | 0.8179 | 0.85 |
| No log | 1.43 | 410 | 0.4870 | 0.8286 | 0.8101 | 0.8192 | 0.8545 |
| No log | 1.46 | 420 | 0.4766 | 0.8171 | 0.7989 | 0.8079 | 0.8455 |
| No log | 1.5 | 430 | 0.4723 | 0.8171 | 0.7989 | 0.8079 | 0.8455 |
| No log | 1.53 | 440 | 0.4675 | 0.8171 | 0.7989 | 0.8079 | 0.8455 |
| No log | 1.57 | 450 | 0.4579 | 0.8305 | 0.8212 | 0.8258 | 0.8636 |
| No log | 1.6 | 460 | 0.4539 | 0.8362 | 0.8268 | 0.8315 | 0.8682 |
| No log | 1.64 | 470 | 0.4505 | 0.8362 | 0.8268 | 0.8315 | 0.8682 |
| No log | 1.67 | 480 | 0.4493 | 0.8514 | 0.8324 | 0.8418 | 0.8773 |
| No log | 1.71 | 490 | 0.4489 | 0.8514 | 0.8324 | 0.8418 | 0.8773 |
| 0.82 | 1.74 | 500 | 0.4487 | 0.8409 | 0.8268 | 0.8338 | 0.8727 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3
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