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---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: LayoutLM_5
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. -->
# LayoutLM_5
This model is a fine-tuned version of [microsoft/layoutlmv3-large](https://huggingface.co/microsoft/layoutlmv3-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3586
- Precision: 0.8344
- Recall: 0.8344
- F1: 0.8344
- Accuracy: 0.9343
## 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-06
- 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: 2000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 3.7 | 100 | 0.8644 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 7.41 | 200 | 0.6214 | 0.7857 | 0.0728 | 0.1333 | 0.8 |
| No log | 11.11 | 300 | 0.4714 | 0.7303 | 0.4305 | 0.5417 | 0.8657 |
| No log | 14.81 | 400 | 0.4046 | 0.7955 | 0.6954 | 0.7420 | 0.9189 |
| 0.6176 | 18.52 | 500 | 0.3755 | 0.8194 | 0.7815 | 0.8000 | 0.9301 |
| 0.6176 | 22.22 | 600 | 0.3611 | 0.7935 | 0.8146 | 0.8039 | 0.9245 |
| 0.6176 | 25.93 | 700 | 0.3679 | 0.7848 | 0.8212 | 0.8026 | 0.9245 |
| 0.6176 | 29.63 | 800 | 0.3292 | 0.8289 | 0.8344 | 0.8317 | 0.9357 |
| 0.6176 | 33.33 | 900 | 0.3408 | 0.8289 | 0.8344 | 0.8317 | 0.9315 |
| 0.1555 | 37.04 | 1000 | 0.3479 | 0.8141 | 0.8411 | 0.8274 | 0.9315 |
| 0.1555 | 40.74 | 1100 | 0.3491 | 0.8247 | 0.8411 | 0.8328 | 0.9357 |
| 0.1555 | 44.44 | 1200 | 0.3704 | 0.7888 | 0.8411 | 0.8141 | 0.9245 |
| 0.1555 | 48.15 | 1300 | 0.3591 | 0.8194 | 0.8411 | 0.8301 | 0.9315 |
| 0.1555 | 51.85 | 1400 | 0.3420 | 0.8344 | 0.8344 | 0.8344 | 0.9343 |
| 0.0746 | 55.56 | 1500 | 0.3546 | 0.8421 | 0.8477 | 0.8449 | 0.9357 |
| 0.0746 | 59.26 | 1600 | 0.3442 | 0.8421 | 0.8477 | 0.8449 | 0.9371 |
| 0.0746 | 62.96 | 1700 | 0.3687 | 0.8205 | 0.8477 | 0.8339 | 0.9357 |
| 0.0746 | 66.67 | 1800 | 0.3743 | 0.8258 | 0.8477 | 0.8366 | 0.9343 |
| 0.0746 | 70.37 | 1900 | 0.3626 | 0.8301 | 0.8411 | 0.8355 | 0.9343 |
| 0.0502 | 74.07 | 2000 | 0.3586 | 0.8344 | 0.8344 | 0.8344 | 0.9343 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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