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---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- cord-layoutlmv3
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-cord_100
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: cord-layoutlmv3
type: cord-layoutlmv3
config: cord
split: test
args: cord
metrics:
- name: Precision
type: precision
value: 0.4115296803652968
- name: Recall
type: recall
value: 0.5396706586826348
- name: F1
type: f1
value: 0.46696891191709844
- name: Accuracy
type: accuracy
value: 0.4350594227504245
---
<!-- 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-cord_100
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the cord-layoutlmv3 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5624
- Precision: 0.4115
- Recall: 0.5397
- F1: 0.4670
- Accuracy: 0.4351
## 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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 0.06 | 10 | 3.8065 | 0.1637 | 0.2582 | 0.2003 | 0.2585 |
| No log | 0.12 | 20 | 3.4787 | 0.4661 | 0.3862 | 0.4224 | 0.3353 |
| No log | 0.19 | 30 | 3.2587 | 0.4332 | 0.4731 | 0.4522 | 0.3667 |
| No log | 0.25 | 40 | 3.0615 | 0.4144 | 0.4873 | 0.4479 | 0.3846 |
| No log | 0.31 | 50 | 2.9052 | 0.3993 | 0.5090 | 0.4475 | 0.4024 |
| No log | 0.38 | 60 | 2.7819 | 0.3876 | 0.5165 | 0.4429 | 0.4143 |
| No log | 0.44 | 70 | 2.6853 | 0.3891 | 0.5202 | 0.4452 | 0.4164 |
| No log | 0.5 | 80 | 2.6245 | 0.3942 | 0.5269 | 0.4510 | 0.4236 |
| No log | 0.56 | 90 | 2.5777 | 0.4056 | 0.5352 | 0.4614 | 0.4312 |
| No log | 0.62 | 100 | 2.5624 | 0.4115 | 0.5397 | 0.4670 | 0.4351 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cpu
- Datasets 2.12.0
- Tokenizers 0.13.3
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