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---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: doc_classification
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. -->
# doc_classification
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0056
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
## 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: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 8.33 | 100 | 0.3533 | 0.4147 | 0.3516 | 0.3805 | 0.8964 |
| No log | 16.67 | 200 | 0.0993 | 0.884 | 0.8633 | 0.8735 | 0.9782 |
| No log | 25.0 | 300 | 0.0338 | 0.9882 | 0.9805 | 0.9843 | 0.9977 |
| No log | 33.33 | 400 | 0.0173 | 0.9961 | 0.9922 | 0.9941 | 0.9992 |
| 0.238 | 41.67 | 500 | 0.0109 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.238 | 50.0 | 600 | 0.0081 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.238 | 58.33 | 700 | 0.0068 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.238 | 66.67 | 800 | 0.0061 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.238 | 75.0 | 900 | 0.0057 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0136 | 83.33 | 1000 | 0.0056 | 1.0 | 1.0 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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