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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: project-ocr
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: 0.7515745276417075
- name: Recall
type: recall
value: 0.8038922155688623
- name: F1
type: f1
value: 0.7768535262206148
- name: Accuracy
type: accuracy
value: 0.8102716468590832
---
<!-- 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. -->
# project-ocr
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: 0.9877
- Precision: 0.7516
- Recall: 0.8039
- F1: 0.7769
- Accuracy: 0.8103
## 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: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 0.83 | 50 | 2.6184 | 0.4355 | 0.5404 | 0.4823 | 0.4338 |
| No log | 1.67 | 100 | 1.8766 | 0.5912 | 0.6018 | 0.5964 | 0.5620 |
| No log | 2.5 | 150 | 1.6165 | 0.5737 | 0.6347 | 0.6027 | 0.6150 |
| No log | 3.33 | 200 | 1.4317 | 0.5732 | 0.6737 | 0.6194 | 0.6944 |
| No log | 4.17 | 250 | 1.2787 | 0.6190 | 0.7126 | 0.6625 | 0.7347 |
| No log | 5.0 | 300 | 1.1632 | 0.6729 | 0.7560 | 0.7120 | 0.7759 |
| No log | 5.83 | 350 | 1.0990 | 0.6980 | 0.7665 | 0.7306 | 0.7857 |
| No log | 6.67 | 400 | 1.0327 | 0.7125 | 0.7792 | 0.7444 | 0.7946 |
| No log | 7.5 | 450 | 0.9994 | 0.7526 | 0.8016 | 0.7764 | 0.8065 |
| 1.6589 | 8.33 | 500 | 0.9877 | 0.7516 | 0.8039 | 0.7769 | 0.8103 |
### Framework versions
- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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